diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/arf/arf-c20-20260324_073259/input_snapshot.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/arf/arf-c20-20260324_073259/input_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..43f00088fb3ebe8537897f32fe47768edd1229db
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/arf/arf-c20-20260324_073259/input_snapshot.json
@@ -0,0 +1,36 @@
+{
+  "dataset_id": "c20",
+  "model": "arf",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-train.csv",
+      "exists": true,
+      "size": 537948,
+      "sha256": "7b491c9989a22d06db0c24422e76bf1d73173a7ba1760d5a3c4e5768c868ac21"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-val.csv",
+      "exists": true,
+      "size": 67338,
+      "sha256": "82d69efb2fbd8ddf6e8d77d9070b3d299f619fded74e2956d3af4b34a9c95a75"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-test.csv",
+      "exists": true,
+      "size": 67368,
+      "sha256": "ab311b2ccc419e2b1423bd27d4079912f464405ef8d37cd87e73ad147ed787ec"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c20/c20-dataset_profile.json",
+      "exists": true,
+      "size": 3686,
+      "sha256": "64a935250a31399f41982c61828d40ab90791bab84e8dc6201dbdfa4508092b8"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c20/c20-dataset_contract_v1.json",
+      "exists": true,
+      "size": 3867,
+      "sha256": "78c743a19951022e3cbae86814578ff8723146c3d216423edc4b94e1b233ad27"
+    }
+  }
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/realtabformer/rtf-c20-20260329_231509/train_20260329_231510.log b/SynthesizePipeline_Archive/output-SpecializedModels/c20/realtabformer/rtf-c20-20260329_231509/train_20260329_231510.log
new file mode 100644
index 0000000000000000000000000000000000000000..4680e4a9c324824dd666e57d4c1479e3155dcd22
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/realtabformer/rtf-c20-20260329_231509/train_20260329_231510.log
@@ -0,0 +1,123998 @@
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+                                                      
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+                                                      
+
+  0%|          | 200/112100 [00:37<4:45:53,  6.52it/s]{'loss': '1.326', 'grad_norm': '1.79', 'learning_rate': '4.991e-05', 'epoch': '0.1785'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                      
+
+  0%|          | 300/112100 [00:55<4:57:11,  6.27it/s]{'loss': '1.308', 'grad_norm': '1.467', 'learning_rate': '4.987e-05', 'epoch': '0.2677'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
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+                                                      
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.296', 'grad_norm': '1.615', 'learning_rate': '4.982e-05', 'epoch': '0.357'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.67it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.67it/s]
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+                                                      
+
+  0%|          | 500/112100 [01:32<5:09:15,  6.01it/s]{'loss': '1.285', 'grad_norm': '1.906', 'learning_rate': '4.978e-05', 'epoch': '0.4462'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+
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+                                                      
+
+  1%|          | 600/112100 [01:51<5:58:54,  5.18it/s]{'loss': '1.277', 'grad_norm': '1.515', 'learning_rate': '4.973e-05', 'epoch': '0.5355'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
+  1%|          | 601/112100 [01:53<24:39:04,  1.26it/s]
+  1%|          | 602/112100 [01:53<19:30:00,  1.59it/s]
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+                                                      
+
+  1%|          | 700/112100 [02:13<6:28:50,  4.77it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.27', 'grad_norm': '1.39', 'learning_rate': '4.969e-05', 'epoch': '0.6247'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
+
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+                                                      
+
+  1%|          | 800/112100 [02:33<6:38:52,  4.65it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.27', 'grad_norm': '1.882', 'learning_rate': '4.964e-05', 'epoch': '0.714'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
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+  1%|          | 900/112100 [02:54<5:21:10,  5.77it/s]
+                                                      
+
+  1%|          | 900/112100 [02:54<5:21:10,  5.77it/s]{'loss': '1.265', 'grad_norm': '1.677', 'learning_rate': '4.96e-05', 'epoch': '0.8032'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
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+  1%|          | 998/112100 [03:14<6:21:27,  4.85it/s]
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+  1%|          | 1000/112100 [03:15<6:14:09,  4.95it/s]
+                                                       
+
+  1%|          | 1000/112100 [03:15<6:14:09,  4.95it/s]{'loss': '1.259', 'grad_norm': '1.645', 'learning_rate': '4.955e-05', 'epoch': '0.8925'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+
+  1%|          | 1001/112100 [03:17<26:32:14,  1.16it/s]
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+                                                       
+
+  1%|          | 1100/112100 [03:34<6:35:59,  4.67it/s]{'loss': '1.26', 'grad_norm': '1.365', 'learning_rate': '4.951e-05', 'epoch': '0.9817'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
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+  1%|          | 1200/112100 [03:58<5:09:05,  5.98it/s]
+                                                       
+
+  1%|          | 1200/112100 [03:58<5:09:05,  5.98it/s]{'loss': '1.255', 'grad_norm': '1.695', 'learning_rate': '4.947e-05', 'epoch': '1.071'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+
+  1%|          | 1201/112100 [04:00<24:33:15,  1.25it/s]
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+  1%|          | 1295/112100 [04:19<6:19:20,  4.87it/s]
+  1%|          | 1296/112100 [04:19<6:34:50,  4.68it/s]
+  1%|          | 1297/112100 [04:19<6:30:10,  4.73it/s]
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+  1%|          | 1300/112100 [04:20<6:29:23,  4.74it/s]
+                                                       
+
+  1%|          | 1300/112100 [04:20<6:29:23,  4.74it/s]{'loss': '1.258', 'grad_norm': '1.337', 'learning_rate': '4.942e-05', 'epoch': '1.16'}
+
+
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+
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+                                                       
+
+  1%|          | 1400/112100 [04:41<5:22:16,  5.72it/s]{'loss': '1.254', 'grad_norm': '1.627', 'learning_rate': '4.938e-05', 'epoch': '1.249'}
+
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+                                                       
+
+  1%|▏         | 1500/112100 [05:03<5:44:25,  5.35it/s]{'loss': '1.253', 'grad_norm': '1.68', 'learning_rate': '4.933e-05', 'epoch': '1.338'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                       
+
+  1%|▏         | 1600/112100 [05:24<5:51:28,  5.24it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.253', 'grad_norm': '1.398', 'learning_rate': '4.929e-05', 'epoch': '1.427'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.67it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.67it/s]
+
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+                                                       
+
+  2%|▏         | 1700/112100 [05:46<5:31:44,  5.55it/s]{'loss': '1.25', 'grad_norm': '1.517', 'learning_rate': '4.924e-05', 'epoch': '1.517'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+
+  2%|▏         | 1701/112100 [05:48<22:04:52,  1.39it/s]
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+  2%|▏         | 1796/112100 [06:07<6:29:20,  4.72it/s]
+  2%|▏         | 1797/112100 [06:07<6:32:25,  4.68it/s]
+  2%|▏         | 1798/112100 [06:07<6:33:41,  4.67it/s]
+  2%|▏         | 1799/112100 [06:07<6:42:48,  4.56it/s]
+  2%|▏         | 1800/112100 [06:08<6:48:26,  4.50it/s]
+                                                       
+
+  2%|▏         | 1800/112100 [06:08<6:48:26,  4.50it/s]{'loss': '1.247', 'grad_norm': '1.656', 'learning_rate': '4.92e-05', 'epoch': '1.606'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
+  2%|▏         | 1801/112100 [06:10<23:16:37,  1.32it/s]
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+  2%|▏         | 1807/112100 [06:11<8:15:14,  3.71it/s]
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+  2%|▏         | 1809/112100 [06:11<7:20:59,  4.17it/s]
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+  2%|▏         | 1840/112100 [06:18<6:10:10,  4.96it/s]
+  2%|▏         | 1841/112100 [06:18<5:56:29,  5.15it/s]
+  2%|▏         | 1842/112100 [06:18<5:47:47,  5.28it/s]
+  2%|▏         | 1843/112100 [06:18<5:42:22,  5.37it/s]
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+  2%|▏         | 1845/112100 [06:19<5:35:56,  5.47it/s]
+  2%|▏         | 1846/112100 [06:19<5:32:48,  5.52it/s]
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+  2%|▏         | 1848/112100 [06:19<5:23:54,  5.67it/s]
+  2%|▏         | 1849/112100 [06:19<5:23:22,  5.68it/s]
+  2%|▏         | 1850/112100 [06:20<5:26:18,  5.63it/s]
+  2%|▏         | 1851/112100 [06:20<5:20:57,  5.72it/s]
+  2%|▏         | 1852/112100 [06:20<5:19:11,  5.76it/s]
+  2%|▏         | 1853/112100 [06:20<5:24:24,  5.66it/s]
+  2%|▏         | 1854/112100 [06:20<5:23:25,  5.68it/s]
+  2%|▏         | 1855/112100 [06:20<5:17:40,  5.78it/s]
+  2%|▏         | 1856/112100 [06:21<5:16:24,  5.81it/s]
+  2%|▏         | 1857/112100 [06:21<5:13:44,  5.86it/s]
+  2%|▏         | 1858/112100 [06:21<5:13:24,  5.86it/s]
+  2%|▏         | 1859/112100 [06:21<5:12:02,  5.89it/s]
+  2%|▏         | 1860/112100 [06:21<5:12:46,  5.87it/s]
+  2%|▏         | 1861/112100 [06:21<5:12:15,  5.88it/s]
+  2%|▏         | 1862/112100 [06:22<5:12:36,  5.88it/s]
+  2%|▏         | 1863/112100 [06:22<5:13:28,  5.86it/s]
+  2%|▏         | 1864/112100 [06:22<5:15:59,  5.81it/s]
+  2%|▏         | 1865/112100 [06:22<5:19:41,  5.75it/s]
+  2%|▏         | 1866/112100 [06:22<5:20:54,  5.73it/s]
+  2%|▏         | 1867/112100 [06:22<5:24:11,  5.67it/s]
+  2%|▏         | 1868/112100 [06:23<5:26:17,  5.63it/s]
+  2%|▏         | 1869/112100 [06:23<5:27:33,  5.61it/s]
+  2%|▏         | 1870/112100 [06:23<5:29:04,  5.58it/s]
+  2%|▏         | 1871/112100 [06:23<5:29:34,  5.57it/s]
+  2%|▏         | 1872/112100 [06:23<5:29:48,  5.57it/s]
+  2%|▏         | 1873/112100 [06:24<5:29:43,  5.57it/s]
+  2%|▏         | 1874/112100 [06:24<5:27:44,  5.61it/s]
+  2%|▏         | 1875/112100 [06:24<5:26:00,  5.63it/s]
+  2%|▏         | 1876/112100 [06:24<5:24:34,  5.66it/s]
+  2%|▏         | 1877/112100 [06:24<5:23:53,  5.67it/s]
+  2%|▏         | 1878/112100 [06:24<5:19:24,  5.75it/s]
+  2%|▏         | 1879/112100 [06:25<5:13:39,  5.86it/s]
+  2%|▏         | 1880/112100 [06:25<5:11:48,  5.89it/s]
+  2%|▏         | 1881/112100 [06:25<5:10:21,  5.92it/s]
+  2%|▏         | 1882/112100 [06:25<5:07:06,  5.98it/s]
+  2%|▏         | 1883/112100 [06:25<5:04:53,  6.02it/s]
+  2%|▏         | 1884/112100 [06:25<5:00:17,  6.12it/s]
+  2%|▏         | 1885/112100 [06:26<4:53:59,  6.25it/s]
+  2%|▏         | 1886/112100 [06:26<4:52:18,  6.28it/s]
+  2%|▏         | 1887/112100 [06:26<4:49:06,  6.35it/s]
+  2%|▏         | 1888/112100 [06:26<4:50:12,  6.33it/s]
+  2%|▏         | 1889/112100 [06:26<4:47:45,  6.38it/s]
+  2%|▏         | 1890/112100 [06:26<4:47:50,  6.38it/s]
+  2%|▏         | 1891/112100 [06:26<4:47:15,  6.39it/s]
+  2%|▏         | 1892/112100 [06:27<4:47:42,  6.38it/s]
+  2%|▏         | 1893/112100 [06:27<4:57:21,  6.18it/s]
+  2%|▏         | 1894/112100 [06:27<5:00:54,  6.10it/s]
+  2%|▏         | 1895/112100 [06:27<5:01:05,  6.10it/s]
+  2%|▏         | 1896/112100 [06:27<4:59:07,  6.14it/s]
+  2%|▏         | 1897/112100 [06:27<5:06:26,  5.99it/s]
+  2%|▏         | 1898/112100 [06:28<5:13:50,  5.85it/s]
+  2%|▏         | 1899/112100 [06:28<5:16:39,  5.80it/s]
+  2%|▏         | 1900/112100 [06:28<5:18:57,  5.76it/s]
+                                                       
+
+  2%|▏         | 1900/112100 [06:28<5:18:57,  5.76it/s]{'loss': '1.247', 'grad_norm': '1.567', 'learning_rate': '4.915e-05', 'epoch': '1.695'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
+  2%|▏         | 1901/112100 [06:30<21:44:33,  1.41it/s]
+  2%|▏         | 1902/112100 [06:30<16:47:56,  1.82it/s]
+  2%|▏         | 1903/112100 [06:30<13:20:54,  2.29it/s]
+  2%|▏         | 1904/112100 [06:30<10:56:03,  2.80it/s]
+  2%|▏         | 1905/112100 [06:31<9:29:30,  3.22it/s] 
+  2%|▏         | 1906/112100 [06:31<8:46:57,  3.49it/s]
+  2%|▏         | 1907/112100 [06:31<8:16:21,  3.70it/s]
+  2%|▏         | 1908/112100 [06:31<7:52:50,  3.88it/s]
+  2%|▏         | 1909/112100 [06:32<7:35:26,  4.03it/s]
+  2%|▏         | 1910/112100 [06:32<7:13:09,  4.24it/s]
+  2%|▏         | 1911/112100 [06:32<6:57:54,  4.39it/s]
+  2%|▏         | 1912/112100 [06:32<6:41:44,  4.57it/s]
+  2%|▏         | 1913/112100 [06:32<6:32:29,  4.68it/s]
+  2%|▏         | 1914/112100 [06:33<6:24:41,  4.77it/s]
+  2%|▏         | 1915/112100 [06:33<6:28:00,  4.73it/s]
+  2%|▏         | 1916/112100 [06:33<6:25:37,  4.76it/s]
+  2%|▏         | 1917/112100 [06:33<6:21:40,  4.81it/s]
+  2%|▏         | 1918/112100 [06:33<6:17:57,  4.86it/s]
+  2%|▏         | 1919/112100 [06:34<6:14:20,  4.91it/s]
+  2%|▏         | 1920/112100 [06:34<6:15:04,  4.90it/s]
+  2%|▏         | 1921/112100 [06:34<6:12:00,  4.94it/s]
+  2%|▏         | 1922/112100 [06:34<6:11:39,  4.94it/s]
+  2%|▏         | 1923/112100 [06:34<6:09:59,  4.96it/s]
+  2%|▏         | 1924/112100 [06:35<6:09:36,  4.97it/s]
+  2%|▏         | 1925/112100 [06:35<6:08:40,  4.98it/s]
+  2%|▏         | 1926/112100 [06:35<6:07:15,  5.00it/s]
+  2%|▏         | 1927/112100 [06:35<6:12:52,  4.92it/s]
+  2%|▏         | 1928/112100 [06:35<6:16:31,  4.88it/s]
+  2%|▏         | 1929/112100 [06:36<6:18:00,  4.86it/s]
+  2%|▏         | 1930/112100 [06:36<6:26:23,  4.75it/s]
+  2%|▏         | 1931/112100 [06:36<6:35:36,  4.64it/s]
+  2%|▏         | 1932/112100 [06:36<6:30:37,  4.70it/s]
+  2%|▏         | 1933/112100 [06:37<6:28:24,  4.73it/s]
+  2%|▏         | 1934/112100 [06:37<6:28:33,  4.73it/s]
+  2%|▏         | 1935/112100 [06:37<6:28:04,  4.73it/s]
+  2%|▏         | 1936/112100 [06:37<6:41:51,  4.57it/s]
+  2%|▏         | 1937/112100 [06:37<6:48:17,  4.50it/s]
+  2%|▏         | 1938/112100 [06:38<6:52:14,  4.45it/s]
+  2%|▏         | 1939/112100 [06:38<6:55:15,  4.42it/s]
+  2%|▏         | 1940/112100 [06:38<6:56:33,  4.41it/s]
+  2%|▏         | 1941/112100 [06:38<6:57:53,  4.39it/s]
+  2%|▏         | 1942/112100 [06:39<6:58:28,  4.39it/s]
+  2%|▏         | 1943/112100 [06:39<6:59:00,  4.38it/s]
+  2%|▏         | 1944/112100 [06:39<6:59:36,  4.38it/s]
+  2%|▏         | 1945/112100 [06:39<7:01:29,  4.36it/s]
+  2%|▏         | 1946/112100 [06:39<6:57:04,  4.40it/s]
+  2%|▏         | 1947/112100 [06:40<6:53:30,  4.44it/s]
+  2%|▏         | 1948/112100 [06:40<6:47:56,  4.50it/s]
+  2%|▏         | 1949/112100 [06:40<6:42:45,  4.56it/s]
+  2%|▏         | 1950/112100 [06:40<6:43:39,  4.55it/s]
+  2%|▏         | 1951/112100 [06:41<6:42:16,  4.56it/s]
+  2%|▏         | 1952/112100 [06:41<6:48:03,  4.50it/s]
+  2%|▏         | 1953/112100 [06:41<6:45:28,  4.53it/s]
+  2%|▏         | 1954/112100 [06:41<6:35:38,  4.64it/s]
+  2%|▏         | 1955/112100 [06:41<6:27:09,  4.74it/s]
+  2%|▏         | 1956/112100 [06:42<6:14:30,  4.90it/s]
+  2%|▏         | 1957/112100 [06:42<6:03:00,  5.06it/s]
+  2%|▏         | 1958/112100 [06:42<6:06:14,  5.01it/s]
+  2%|▏         | 1959/112100 [06:42<6:08:56,  4.98it/s]
+  2%|▏         | 1960/112100 [06:42<6:08:07,  4.99it/s]
+  2%|▏         | 1961/112100 [06:43<6:08:28,  4.98it/s]
+  2%|▏         | 1962/112100 [06:43<6:12:00,  4.93it/s]
+  2%|▏         | 1963/112100 [06:43<6:12:27,  4.93it/s]
+  2%|▏         | 1964/112100 [06:43<6:12:44,  4.92it/s]
+  2%|▏         | 1965/112100 [06:43<6:10:54,  4.95it/s]
+  2%|▏         | 1966/112100 [06:44<6:13:35,  4.91it/s]
+  2%|▏         | 1967/112100 [06:44<6:22:48,  4.79it/s]
+  2%|▏         | 1968/112100 [06:44<6:28:26,  4.73it/s]
+  2%|▏         | 1969/112100 [06:44<6:28:42,  4.72it/s]
+  2%|▏         | 1970/112100 [06:44<6:32:14,  4.68it/s]
+  2%|▏         | 1971/112100 [06:45<6:32:33,  4.68it/s]
+  2%|▏         | 1972/112100 [06:45<6:39:48,  4.59it/s]
+  2%|▏         | 1973/112100 [06:45<6:36:29,  4.63it/s]
+  2%|▏         | 1974/112100 [06:45<6:31:40,  4.69it/s]
+  2%|▏         | 1975/112100 [06:46<6:30:49,  4.70it/s]
+  2%|▏         | 1976/112100 [06:46<6:35:22,  4.64it/s]
+  2%|▏         | 1977/112100 [06:46<6:35:51,  4.64it/s]
+  2%|▏         | 1978/112100 [06:46<6:38:32,  4.61it/s]
+  2%|▏         | 1979/112100 [06:46<6:35:03,  4.65it/s]
+  2%|▏         | 1980/112100 [06:47<6:34:01,  4.66it/s]
+  2%|▏         | 1981/112100 [06:47<6:37:24,  4.62it/s]
+  2%|▏         | 1982/112100 [06:47<6:34:50,  4.65it/s]
+  2%|▏         | 1983/112100 [06:47<6:34:19,  4.65it/s]
+  2%|▏         | 1984/112100 [06:47<6:33:58,  4.66it/s]
+  2%|▏         | 1985/112100 [06:48<6:25:18,  4.76it/s]
+  2%|▏         | 1986/112100 [06:48<6:19:40,  4.83it/s]
+  2%|▏         | 1987/112100 [06:48<6:19:09,  4.84it/s]
+  2%|▏         | 1988/112100 [06:48<6:17:56,  4.86it/s]
+  2%|▏         | 1989/112100 [06:49<6:17:55,  4.86it/s]
+  2%|▏         | 1990/112100 [06:49<6:23:16,  4.79it/s]
+  2%|▏         | 1991/112100 [06:49<6:31:05,  4.69it/s]
+  2%|▏         | 1992/112100 [06:49<6:34:03,  4.66it/s]
+  2%|▏         | 1993/112100 [06:49<6:33:54,  4.66it/s]
+  2%|▏         | 1994/112100 [06:50<6:29:07,  4.72it/s]
+  2%|▏         | 1995/112100 [06:50<6:25:41,  4.76it/s]
+  2%|▏         | 1996/112100 [06:50<6:21:22,  4.81it/s]
+  2%|▏         | 1997/112100 [06:50<6:26:42,  4.75it/s]
+  2%|▏         | 1998/112100 [06:50<6:30:59,  4.69it/s]
+  2%|▏         | 1999/112100 [06:51<6:33:05,  4.67it/s]
+  2%|▏         | 2000/112100 [06:51<6:29:04,  4.72it/s]
+                                                       
+
+  2%|▏         | 2000/112100 [06:51<6:29:04,  4.72it/s]{'loss': '1.247', 'grad_norm': '1.566', 'learning_rate': '4.911e-05', 'epoch': '1.784'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
+  2%|▏         | 2001/112100 [06:53<23:03:51,  1.33it/s]
+  2%|▏         | 2002/112100 [06:53<18:08:33,  1.69it/s]
+  2%|▏         | 2003/112100 [06:53<14:41:26,  2.08it/s]
+  2%|▏         | 2004/112100 [06:54<12:12:31,  2.50it/s]
+  2%|▏         | 2005/112100 [06:54<10:34:20,  2.89it/s]
+  2%|▏         | 2006/112100 [06:54<9:06:03,  3.36it/s] 
+  2%|▏         | 2007/112100 [06:54<7:59:13,  3.83it/s]
+  2%|▏         | 2008/112100 [06:54<7:12:29,  4.24it/s]
+  2%|▏         | 2009/112100 [06:54<6:40:21,  4.58it/s]
+  2%|▏         | 2010/112100 [06:55<6:16:33,  4.87it/s]
+  2%|▏         | 2011/112100 [06:55<5:59:19,  5.11it/s]
+  2%|▏         | 2012/112100 [06:55<5:48:14,  5.27it/s]
+  2%|▏         | 2013/112100 [06:55<5:41:28,  5.37it/s]
+  2%|▏         | 2014/112100 [06:55<5:32:52,  5.51it/s]
+  2%|▏         | 2015/112100 [06:56<5:27:34,  5.60it/s]
+  2%|▏         | 2016/112100 [06:56<5:25:05,  5.64it/s]
+  2%|▏         | 2017/112100 [06:56<5:24:00,  5.66it/s]
+  2%|▏         | 2018/112100 [06:56<5:21:08,  5.71it/s]
+  2%|▏         | 2019/112100 [06:56<5:20:35,  5.72it/s]
+  2%|▏         | 2020/112100 [06:56<5:19:03,  5.75it/s]
+  2%|▏         | 2021/112100 [06:57<5:16:35,  5.79it/s]
+  2%|▏         | 2022/112100 [06:57<5:11:54,  5.88it/s]
+  2%|▏         | 2023/112100 [06:57<5:10:55,  5.90it/s]
+  2%|▏         | 2024/112100 [06:57<5:10:56,  5.90it/s]
+  2%|▏         | 2025/112100 [06:57<5:09:55,  5.92it/s]
+  2%|▏         | 2026/112100 [06:57<5:08:22,  5.95it/s]
+  2%|▏         | 2027/112100 [06:58<5:04:58,  6.02it/s]
+  2%|▏         | 2028/112100 [06:58<5:01:28,  6.09it/s]
+  2%|▏         | 2029/112100 [06:58<4:58:23,  6.15it/s]
+  2%|▏         | 2030/112100 [06:58<4:56:11,  6.19it/s]
+  2%|▏         | 2031/112100 [06:58<4:56:28,  6.19it/s]
+  2%|▏         | 2032/112100 [06:58<4:55:30,  6.21it/s]
+  2%|▏         | 2033/112100 [06:58<4:56:04,  6.20it/s]
+  2%|▏         | 2034/112100 [06:59<4:55:30,  6.21it/s]
+  2%|▏         | 2035/112100 [06:59<4:56:35,  6.19it/s]
+  2%|▏         | 2036/112100 [06:59<4:58:18,  6.15it/s]
+  2%|▏         | 2037/112100 [06:59<4:57:12,  6.17it/s]
+  2%|▏         | 2038/112100 [06:59<4:56:09,  6.19it/s]
+  2%|▏         | 2039/112100 [06:59<4:55:26,  6.21it/s]
+  2%|▏         | 2040/112100 [07:00<5:04:25,  6.03it/s]
+  2%|▏         | 2041/112100 [07:00<5:09:59,  5.92it/s]
+  2%|▏         | 2042/112100 [07:00<5:13:47,  5.85it/s]
+  2%|▏         | 2043/112100 [07:00<5:14:36,  5.83it/s]
+  2%|▏         | 2044/112100 [07:00<5:14:46,  5.83it/s]
+  2%|▏         | 2045/112100 [07:01<5:19:42,  5.74it/s]
+  2%|▏         | 2046/112100 [07:01<5:21:56,  5.70it/s]
+  2%|▏         | 2047/112100 [07:01<5:25:40,  5.63it/s]
+  2%|▏         | 2048/112100 [07:01<5:27:23,  5.60it/s]
+  2%|▏         | 2049/112100 [07:01<5:27:34,  5.60it/s]
+  2%|▏         | 2050/112100 [07:01<5:24:26,  5.65it/s]
+  2%|▏         | 2051/112100 [07:02<5:24:30,  5.65it/s]
+  2%|▏         | 2052/112100 [07:02<5:24:52,  5.65it/s]
+  2%|▏         | 2053/112100 [07:02<5:25:38,  5.63it/s]
+  2%|▏         | 2054/112100 [07:02<5:26:29,  5.62it/s]
+  2%|▏         | 2055/112100 [07:02<5:25:36,  5.63it/s]
+  2%|▏         | 2056/112100 [07:02<5:25:14,  5.64it/s]
+  2%|▏         | 2057/112100 [07:03<5:27:25,  5.60it/s]
+  2%|▏         | 2058/112100 [07:03<5:19:11,  5.75it/s]
+  2%|▏         | 2059/112100 [07:03<5:15:54,  5.81it/s]
+  2%|▏         | 2060/112100 [07:03<5:12:59,  5.86it/s]
+  2%|▏         | 2061/112100 [07:03<5:08:03,  5.95it/s]
+  2%|▏         | 2062/112100 [07:03<5:06:56,  5.98it/s]
+  2%|▏         | 2063/112100 [07:04<5:07:54,  5.96it/s]
+  2%|▏         | 2064/112100 [07:04<5:08:23,  5.95it/s]
+  2%|▏         | 2065/112100 [07:04<5:07:46,  5.96it/s]
+  2%|▏         | 2066/112100 [07:04<5:10:47,  5.90it/s]
+  2%|▏         | 2067/112100 [07:04<5:02:43,  6.06it/s]
+  2%|▏         | 2068/112100 [07:04<5:05:38,  6.00it/s]
+  2%|▏         | 2069/112100 [07:05<5:01:39,  6.08it/s]
+  2%|▏         | 2070/112100 [07:05<5:05:10,  6.01it/s]
+  2%|▏         | 2071/112100 [07:05<5:14:53,  5.82it/s]
+  2%|▏         | 2072/112100 [07:05<5:19:05,  5.75it/s]
+  2%|▏         | 2073/112100 [07:05<5:24:14,  5.66it/s]
+  2%|▏         | 2074/112100 [07:06<5:24:41,  5.65it/s]
+  2%|▏         | 2075/112100 [07:06<5:21:13,  5.71it/s]
+  2%|▏         | 2076/112100 [07:06<5:25:11,  5.64it/s]
+  2%|▏         | 2077/112100 [07:06<5:29:56,  5.56it/s]
+  2%|▏         | 2078/112100 [07:06<5:31:20,  5.53it/s]
+  2%|▏         | 2079/112100 [07:06<5:32:37,  5.51it/s]
+  2%|▏         | 2080/112100 [07:07<5:41:33,  5.37it/s]
+  2%|▏         | 2081/112100 [07:07<5:57:48,  5.12it/s]
+  2%|▏         | 2082/112100 [07:07<6:04:49,  5.03it/s]
+  2%|▏         | 2083/112100 [07:07<6:02:42,  5.06it/s]
+  2%|▏         | 2084/112100 [07:07<6:02:48,  5.05it/s]
+  2%|▏         | 2085/112100 [07:08<6:11:58,  4.93it/s]
+  2%|▏         | 2086/112100 [07:08<6:18:23,  4.85it/s]
+  2%|▏         | 2087/112100 [07:08<6:22:34,  4.79it/s]
+  2%|▏         | 2088/112100 [07:08<6:23:09,  4.79it/s]
+  2%|▏         | 2089/112100 [07:09<6:25:47,  4.75it/s]
+  2%|▏         | 2090/112100 [07:09<6:28:13,  4.72it/s]
+  2%|▏         | 2091/112100 [07:09<6:28:46,  4.72it/s]
+  2%|▏         | 2092/112100 [07:09<6:28:24,  4.72it/s]
+  2%|▏         | 2093/112100 [07:09<6:28:31,  4.72it/s]
+  2%|▏         | 2094/112100 [07:10<6:28:01,  4.73it/s]
+  2%|▏         | 2095/112100 [07:10<6:34:30,  4.65it/s]
+  2%|▏         | 2096/112100 [07:10<6:29:54,  4.70it/s]
+  2%|▏         | 2097/112100 [07:10<6:31:20,  4.68it/s]
+  2%|▏         | 2098/112100 [07:10<6:25:53,  4.75it/s]
+  2%|▏         | 2099/112100 [07:11<6:19:16,  4.83it/s]
+  2%|▏         | 2100/112100 [07:11<6:19:29,  4.83it/s]
+                                                       
+
+  2%|▏         | 2100/112100 [07:11<6:19:29,  4.83it/s]{'loss': '1.247', 'grad_norm': '1.522', 'learning_rate': '4.906e-05', 'epoch': '1.874'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+
+  2%|▏         | 2101/112100 [07:13<22:51:36,  1.34it/s]
+  2%|▏         | 2102/112100 [07:13<18:10:00,  1.68it/s]
+  2%|▏         | 2103/112100 [07:13<14:56:46,  2.04it/s]
+  2%|▏         | 2104/112100 [07:14<12:26:02,  2.46it/s]
+  2%|▏         | 2105/112100 [07:14<10:36:41,  2.88it/s]
+  2%|▏         | 2106/112100 [07:14<9:21:31,  3.26it/s] 
+  2%|▏         | 2107/112100 [07:14<8:27:36,  3.61it/s]
+  2%|▏         | 2108/112100 [07:14<7:51:31,  3.89it/s]
+  2%|▏         | 2109/112100 [07:15<7:25:57,  4.11it/s]
+  2%|▏         | 2110/112100 [07:15<7:10:18,  4.26it/s]
+  2%|▏         | 2111/112100 [07:15<6:50:06,  4.47it/s]
+  2%|▏         | 2112/112100 [07:15<6:42:26,  4.55it/s]
+  2%|▏         | 2113/112100 [07:15<6:30:19,  4.70it/s]
+  2%|▏         | 2114/112100 [07:16<6:20:39,  4.82it/s]
+  2%|▏         | 2115/112100 [07:16<6:14:37,  4.89it/s]
+  2%|▏         | 2116/112100 [07:16<6:08:49,  4.97it/s]
+  2%|▏         | 2117/112100 [07:16<6:13:30,  4.91it/s]
+  2%|▏         | 2118/112100 [07:16<6:20:56,  4.81it/s]
+  2%|▏         | 2119/112100 [07:17<6:25:32,  4.75it/s]
+  2%|▏         | 2120/112100 [07:17<6:29:44,  4.70it/s]
+  2%|▏         | 2121/112100 [07:17<6:21:17,  4.81it/s]
+  2%|▏         | 2122/112100 [07:17<6:24:12,  4.77it/s]
+  2%|▏         | 2123/112100 [07:17<6:22:37,  4.79it/s]
+  2%|▏         | 2124/112100 [07:18<6:23:04,  4.78it/s]
+  2%|▏         | 2125/112100 [07:18<6:30:11,  4.70it/s]
+  2%|▏         | 2126/112100 [07:18<6:33:08,  4.66it/s]
+  2%|▏         | 2127/112100 [07:18<6:41:14,  4.57it/s]
+  2%|▏         | 2128/112100 [07:19<6:47:48,  4.49it/s]
+  2%|▏         | 2129/112100 [07:19<6:50:02,  4.47it/s]
+  2%|▏         | 2130/112100 [07:19<6:45:19,  4.52it/s]
+  2%|▏         | 2131/112100 [07:19<6:41:47,  4.56it/s]
+  2%|▏         | 2132/112100 [07:19<6:26:11,  4.75it/s]
+  2%|▏         | 2133/112100 [07:20<6:14:22,  4.90it/s]
+  2%|▏         | 2134/112100 [07:20<6:09:37,  4.96it/s]
+  2%|▏         | 2135/112100 [07:20<5:56:08,  5.15it/s]
+  2%|▏         | 2136/112100 [07:20<5:54:13,  5.17it/s]
+  2%|▏         | 2137/112100 [07:20<5:59:11,  5.10it/s]
+  2%|▏         | 2138/112100 [07:21<6:04:29,  5.03it/s]
+  2%|▏         | 2139/112100 [07:21<6:04:37,  5.03it/s]
+  2%|▏         | 2140/112100 [07:21<6:08:17,  4.98it/s]
+  2%|▏         | 2141/112100 [07:21<6:09:11,  4.96it/s]
+  2%|▏         | 2142/112100 [07:21<6:08:08,  4.98it/s]
+  2%|▏         | 2143/112100 [07:22<6:12:28,  4.92it/s]
+  2%|▏         | 2144/112100 [07:22<6:15:41,  4.88it/s]
+  2%|▏         | 2145/112100 [07:22<6:17:08,  4.86it/s]
+  2%|▏         | 2146/112100 [07:22<6:24:57,  4.76it/s]
+  2%|▏         | 2147/112100 [07:22<6:33:00,  4.66it/s]
+  2%|▏         | 2148/112100 [07:23<6:29:09,  4.71it/s]
+  2%|▏         | 2149/112100 [07:23<6:21:56,  4.80it/s]
+  2%|▏         | 2150/112100 [07:23<6:20:26,  4.82it/s]
+  2%|▏         | 2151/112100 [07:23<6:13:48,  4.90it/s]
+  2%|▏         | 2152/112100 [07:23<6:10:36,  4.94it/s]
+  2%|▏         | 2153/112100 [07:24<6:30:55,  4.69it/s]
+  2%|▏         | 2154/112100 [07:24<6:36:13,  4.62it/s]
+  2%|▏         | 2155/112100 [07:24<6:43:39,  4.54it/s]
+  2%|▏         | 2156/112100 [07:24<6:51:12,  4.46it/s]
+  2%|▏         | 2157/112100 [07:25<6:47:57,  4.49it/s]
+  2%|▏         | 2158/112100 [07:25<6:41:41,  4.56it/s]
+  2%|▏         | 2159/112100 [07:25<6:38:13,  4.60it/s]
+  2%|▏         | 2160/112100 [07:25<6:39:05,  4.59it/s]
+  2%|▏         | 2161/112100 [07:25<6:39:21,  4.59it/s]
+  2%|▏         | 2162/112100 [07:26<6:43:32,  4.54it/s]
+  2%|▏         | 2163/112100 [07:26<6:44:43,  4.53it/s]
+  2%|▏         | 2164/112100 [07:26<6:41:58,  4.56it/s]
+  2%|▏         | 2165/112100 [07:26<6:39:00,  4.59it/s]
+  2%|▏         | 2166/112100 [07:27<6:38:37,  4.60it/s]
+  2%|▏         | 2167/112100 [07:27<6:37:40,  4.61it/s]
+  2%|▏         | 2168/112100 [07:27<6:36:04,  4.63it/s]
+  2%|▏         | 2169/112100 [07:27<6:36:56,  4.62it/s]
+  2%|▏         | 2170/112100 [07:27<6:39:09,  4.59it/s]
+  2%|▏         | 2171/112100 [07:28<6:38:26,  4.60it/s]
+  2%|▏         | 2172/112100 [07:28<6:37:37,  4.61it/s]
+  2%|▏         | 2173/112100 [07:28<6:40:05,  4.58it/s]
+  2%|▏         | 2174/112100 [07:28<6:47:42,  4.49it/s]
+  2%|▏         | 2175/112100 [07:29<6:50:27,  4.46it/s]
+  2%|▏         | 2176/112100 [07:29<6:50:36,  4.46it/s]
+  2%|▏         | 2177/112100 [07:29<6:46:25,  4.51it/s]
+  2%|▏         | 2178/112100 [07:29<6:43:13,  4.54it/s]
+  2%|▏         | 2179/112100 [07:29<6:38:47,  4.59it/s]
+  2%|▏         | 2180/112100 [07:30<6:37:58,  4.60it/s]
+  2%|▏         | 2181/112100 [07:30<6:27:35,  4.73it/s]
+  2%|▏         | 2182/112100 [07:30<6:17:03,  4.86it/s]
+  2%|▏         | 2183/112100 [07:30<6:02:05,  5.06it/s]
+  2%|▏         | 2184/112100 [07:30<5:50:10,  5.23it/s]
+  2%|▏         | 2185/112100 [07:31<5:43:54,  5.33it/s]
+  2%|▏         | 2186/112100 [07:31<5:36:46,  5.44it/s]
+  2%|▏         | 2187/112100 [07:31<5:32:10,  5.51it/s]
+  2%|▏         | 2188/112100 [07:31<5:34:12,  5.48it/s]
+  2%|▏         | 2189/112100 [07:31<5:36:09,  5.45it/s]
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+                                                       
+
+  2%|▏         | 2200/112100 [07:33<5:36:07,  5.45it/s]{'loss': '1.248', 'grad_norm': '1.54', 'learning_rate': '4.902e-05', 'epoch': '1.963'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
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+                                                       
+
+  2%|▏         | 2300/112100 [07:57<6:34:07,  4.64it/s]{'loss': '1.243', 'grad_norm': '1.522', 'learning_rate': '4.897e-05', 'epoch': '2.052'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+
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+  2%|▏         | 2392/112100 [08:16<5:19:46,  5.72it/s]
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+  2%|▏         | 2397/112100 [08:17<5:25:09,  5.62it/s]
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+                                                       
+
+  2%|▏         | 2400/112100 [08:18<5:18:22,  5.74it/s]{'loss': '1.243', 'grad_norm': '1.2', 'learning_rate': '4.893e-05', 'epoch': '2.141'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.42it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.42it/s]
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+                                                       
+
+  2%|▏         | 2500/112100 [08:41<6:49:56,  4.46it/s]{'loss': '1.244', 'grad_norm': '1.554', 'learning_rate': '4.889e-05', 'epoch': '2.23'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
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+                                                       
+
+  2%|▏         | 2600/112100 [09:02<6:54:34,  4.40it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.244', 'grad_norm': '1.549', 'learning_rate': '4.884e-05', 'epoch': '2.32'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
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+                                                       
+
+  2%|▏         | 2700/112100 [09:26<5:54:52,  5.14it/s]{'loss': '1.244', 'grad_norm': '1.28', 'learning_rate': '4.88e-05', 'epoch': '2.409'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
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+                                                       
+
+  2%|▏         | 2800/112100 [09:47<6:02:04,  5.03it/s]{'loss': '1.243', 'grad_norm': '1.554', 'learning_rate': '4.875e-05', 'epoch': '2.498'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
+
+  2%|▏         | 2801/112100 [09:49<21:49:11,  1.39it/s]
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+                                                       
+
+  3%|▎         | 2900/112100 [10:10<5:46:24,  5.25it/s]{'loss': '1.242', 'grad_norm': '1.378', 'learning_rate': '4.871e-05', 'epoch': '2.587'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                       
+
+  3%|▎         | 3000/112100 [10:33<6:44:06,  4.50it/s]{'loss': '1.243', 'grad_norm': '1.308', 'learning_rate': '4.866e-05', 'epoch': '2.676'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
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+  3%|▎         | 3001/112100 [10:35<27:11:40,  1.11it/s]
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+  3%|▎         | 3100/112100 [10:54<5:20:18,  5.67it/s]
+                                                       
+
+  3%|▎         | 3100/112100 [10:54<5:20:18,  5.67it/s]{'loss': '1.241', 'grad_norm': '1.441', 'learning_rate': '4.862e-05', 'epoch': '2.766'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+
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+  3%|▎         | 3191/112100 [11:17<6:47:30,  4.45it/s]
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+  3%|▎         | 3196/112100 [11:18<6:45:52,  4.47it/s]
+  3%|▎         | 3197/112100 [11:18<6:50:44,  4.42it/s]
+  3%|▎         | 3198/112100 [11:18<6:52:43,  4.40it/s]
+  3%|▎         | 3199/112100 [11:18<6:56:17,  4.36it/s]
+  3%|▎         | 3200/112100 [11:19<6:55:33,  4.37it/s]
+                                                       
+
+  3%|▎         | 3200/112100 [11:19<6:55:33,  4.37it/s]{'loss': '1.243', 'grad_norm': '1.571', 'learning_rate': '4.857e-05', 'epoch': '2.855'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
+  3%|▎         | 3201/112100 [11:21<27:12:18,  1.11it/s]
+  3%|▎         | 3202/112100 [11:21<20:47:28,  1.45it/s]
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+  3%|▎         | 3207/112100 [11:22<7:59:18,  3.79it/s]
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+  3%|▎         | 3210/112100 [11:23<6:17:36,  4.81it/s]
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+  3%|▎         | 3212/112100 [11:23<5:49:18,  5.20it/s]
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+  3%|▎         | 3221/112100 [11:25<5:03:53,  5.97it/s]
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+                                                       
+
+  3%|▎         | 3300/112100 [11:40<6:46:51,  4.46it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.238', 'grad_norm': '1.398', 'learning_rate': '4.853e-05', 'epoch': '2.944'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+  3%|▎         | 3363/112100 [11:56<6:15:00,  4.83it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
+  3%|▎         | 3364/112100 [11:58<26:31:37,  1.14it/s]
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+  3%|▎         | 3400/112100 [12:05<6:00:30,  5.03it/s]
+                                                       
+
+  3%|▎         | 3400/112100 [12:05<6:00:30,  5.03it/s]{'loss': '1.238', 'grad_norm': '1.69', 'learning_rate': '4.848e-05', 'epoch': '3.033'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
+  3%|▎         | 3401/112100 [12:07<22:01:17,  1.37it/s]
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+  3%|▎         | 3460/112100 [12:19<6:40:34,  4.52it/s]
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+  3%|▎         | 3474/112100 [12:22<6:42:57,  4.49it/s]
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+  3%|▎         | 3478/112100 [12:22<6:29:25,  4.65it/s]
+  3%|▎         | 3479/112100 [12:23<6:23:49,  4.72it/s]
+  3%|▎         | 3480/112100 [12:23<6:27:27,  4.67it/s]
+  3%|▎         | 3481/112100 [12:23<6:26:59,  4.68it/s]
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+  3%|▎         | 3484/112100 [12:24<6:34:39,  4.59it/s]
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+                                                       
+
+  3%|▎         | 3500/112100 [12:27<6:45:40,  4.46it/s]{'loss': '1.238', 'grad_norm': '1.297', 'learning_rate': '4.844e-05', 'epoch': '3.122'}
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
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+                                                       
+
+  3%|▎         | 3600/112100 [12:51<6:16:45,  4.80it/s]{'loss': '1.239', 'grad_norm': '1.855', 'learning_rate': '4.839e-05', 'epoch': '3.212'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                       
+
+  3%|▎         | 3700/112100 [13:15<7:01:53,  4.28it/s]{'loss': '1.239', 'grad_norm': '1.354', 'learning_rate': '4.835e-05', 'epoch': '3.301'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+
+  3%|▎         | 3701/112100 [13:17<23:13:51,  1.30it/s]
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+  3%|▎         | 3800/112100 [13:38<7:01:54,  4.28it/s]
+                                                       
+
+  3%|▎         | 3800/112100 [13:38<7:01:54,  4.28it/s]{'loss': '1.238', 'grad_norm': '1.367', 'learning_rate': '4.831e-05', 'epoch': '3.39'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
+  3%|▎         | 3801/112100 [13:40<24:08:53,  1.25it/s]
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+  3%|▎         | 3861/112100 [13:54<7:21:34,  4.09it/s]
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+  3%|▎         | 3876/112100 [13:58<6:46:14,  4.44it/s]
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+  3%|▎         | 3878/112100 [13:58<6:51:25,  4.38it/s]
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+  3%|▎         | 3891/112100 [14:01<6:42:09,  4.48it/s]
+  3%|▎         | 3892/112100 [14:01<6:40:16,  4.51it/s]
+  3%|▎         | 3893/112100 [14:02<6:33:27,  4.58it/s]
+  3%|▎         | 3894/112100 [14:02<6:34:19,  4.57it/s]
+  3%|▎         | 3895/112100 [14:02<6:35:42,  4.56it/s]
+  3%|▎         | 3896/112100 [14:02<6:41:59,  4.49it/s]
+  3%|▎         | 3897/112100 [14:03<6:49:21,  4.41it/s]
+  3%|▎         | 3898/112100 [14:03<6:45:02,  4.45it/s]
+  3%|▎         | 3899/112100 [14:03<6:48:14,  4.42it/s]
+  3%|▎         | 3900/112100 [14:03<6:52:04,  4.38it/s]
+                                                       
+
+  3%|▎         | 3900/112100 [14:03<6:52:04,  4.38it/s]{'loss': '1.241', 'grad_norm': '1.369', 'learning_rate': '4.826e-05', 'epoch': '3.479'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+
+  3%|▎         | 3901/112100 [14:05<22:57:39,  1.31it/s]
+  3%|▎         | 3902/112100 [14:05<17:56:23,  1.68it/s]
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+  3%|▎         | 3907/112100 [14:06<8:09:34,  3.68it/s]
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+  3%|▎         | 3909/112100 [14:07<7:01:34,  4.28it/s]
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+                                                       
+
+  4%|▎         | 4000/112100 [14:26<6:59:04,  4.30it/s]{'loss': '1.237', 'grad_norm': '1.52', 'learning_rate': '4.822e-05', 'epoch': '3.568'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
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+  4%|▎         | 4093/112100 [14:49<5:35:13,  5.37it/s]
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+  4%|▎         | 4096/112100 [14:50<5:30:18,  5.45it/s]
+  4%|▎         | 4097/112100 [14:50<5:28:54,  5.47it/s]
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+  4%|▎         | 4100/112100 [14:51<5:35:59,  5.36it/s]
+                                                       
+
+  4%|▎         | 4100/112100 [14:51<5:35:59,  5.36it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.238', 'grad_norm': '1.689', 'learning_rate': '4.817e-05', 'epoch': '3.658'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+
+  4%|▎         | 4101/112100 [14:53<25:25:51,  1.18it/s]
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+                                                       
+
+  4%|▎         | 4200/112100 [15:15<6:24:32,  4.68it/s]{'loss': '1.236', 'grad_norm': '1.439', 'learning_rate': '4.813e-05', 'epoch': '3.747'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.43it/s]
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+                                                       
+
+  4%|▍         | 4300/112100 [15:39<5:34:30,  5.37it/s]{'loss': '1.236', 'grad_norm': '1.295', 'learning_rate': '4.808e-05', 'epoch': '3.836'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                       
+
+  4%|▍         | 4400/112100 [16:03<6:54:45,  4.33it/s]{'loss': '1.238', 'grad_norm': '1.408', 'learning_rate': '4.804e-05', 'epoch': '3.925'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                       
+
+  4%|▍         | 4500/112100 [16:29<6:44:12,  4.44it/s]{'loss': '1.238', 'grad_norm': '1.291', 'learning_rate': '4.799e-05', 'epoch': '4.014'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                       
+
+  4%|▍         | 4600/112100 [16:54<6:25:46,  4.64it/s]{'loss': '1.237', 'grad_norm': '1.047', 'learning_rate': '4.795e-05', 'epoch': '4.104'}
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                       
+
+  4%|▍         | 4700/112100 [17:18<6:42:47,  4.44it/s]{'loss': '1.234', 'grad_norm': '1.549', 'learning_rate': '4.79e-05', 'epoch': '4.193'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                       
+
+  4%|▍         | 4800/112100 [17:42<5:35:32,  5.33it/s]{'loss': '1.236', 'grad_norm': '1.261', 'learning_rate': '4.786e-05', 'epoch': '4.282'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                       
+
+  4%|▍         | 4900/112100 [18:05<6:35:29,  4.52it/s]{'loss': '1.234', 'grad_norm': '1.082', 'learning_rate': '4.781e-05', 'epoch': '4.371'}
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                       
+
+  4%|▍         | 5000/112100 [18:29<5:12:57,  5.70it/s]{'loss': '1.234', 'grad_norm': '1.117', 'learning_rate': '4.777e-05', 'epoch': '4.461'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                       
+
+  5%|▍         | 5100/112100 [18:54<6:48:38,  4.36it/s]{'loss': '1.236', 'grad_norm': '1.461', 'learning_rate': '4.773e-05', 'epoch': '4.55'}
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
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+                                                       
+
+  5%|▍         | 5200/112100 [19:17<5:53:42,  5.04it/s]{'loss': '1.235', 'grad_norm': '1.683', 'learning_rate': '4.768e-05', 'epoch': '4.639'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                       
+
+  5%|▍         | 5300/112100 [19:43<7:04:18,  4.20it/s]{'loss': '1.235', 'grad_norm': '1.564', 'learning_rate': '4.764e-05', 'epoch': '4.728'}
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.35it/s]
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+                                                       
+
+  5%|▍         | 5400/112100 [20:05<7:09:58,  4.14it/s]{'loss': '1.235', 'grad_norm': '1.427', 'learning_rate': '4.759e-05', 'epoch': '4.817'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                       
+
+  5%|▍         | 5500/112100 [20:31<6:42:38,  4.41it/s]{'loss': '1.235', 'grad_norm': '1.237', 'learning_rate': '4.755e-05', 'epoch': '4.907'}
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+                                                       
+
+  5%|▍         | 5600/112100 [20:54<7:17:32,  4.06it/s]{'loss': '1.234', 'grad_norm': '1.458', 'learning_rate': '4.75e-05', 'epoch': '4.996'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                       
+
+  5%|▌         | 5700/112100 [21:20<5:08:22,  5.75it/s]{'loss': '1.235', 'grad_norm': '1.3', 'learning_rate': '4.746e-05', 'epoch': '5.085'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                       
+
+  5%|▌         | 5800/112100 [21:44<6:07:46,  4.82it/s]{'loss': '1.235', 'grad_norm': '1.757', 'learning_rate': '4.741e-05', 'epoch': '5.174'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+
+  5%|▌         | 5801/112100 [21:47<25:57:02,  1.14it/s]
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+                                                       
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.231', 'grad_norm': '1.248', 'learning_rate': '4.737e-05', 'epoch': '5.263'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                       
+
+  5%|▌         | 6000/112100 [22:33<6:06:05,  4.83it/s]{'loss': '1.233', 'grad_norm': '1.249', 'learning_rate': '4.732e-05', 'epoch': '5.353'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                       
+
+  5%|▌         | 6100/112100 [22:56<6:17:55,  4.67it/s]{'loss': '1.231', 'grad_norm': '1.256', 'learning_rate': '4.728e-05', 'epoch': '5.442'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                       
+
+  6%|▌         | 6200/112100 [23:19<5:46:18,  5.10it/s]{'loss': '1.234', 'grad_norm': '1.221', 'learning_rate': '4.724e-05', 'epoch': '5.531'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+  6%|▌         | 6297/112100 [23:42<5:16:48,  5.57it/s]
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+  6%|▌         | 6300/112100 [23:43<5:10:08,  5.69it/s]
+                                                       
+
+  6%|▌         | 6300/112100 [23:43<5:10:08,  5.69it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.233', 'grad_norm': '1.397', 'learning_rate': '4.719e-05', 'epoch': '5.62'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
+  6%|▌         | 6301/112100 [23:45<24:33:03,  1.20it/s]
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+                                                       
+
+  6%|▌         | 6400/112100 [24:08<6:19:29,  4.64it/s]{'loss': '1.231', 'grad_norm': '1.266', 'learning_rate': '4.715e-05', 'epoch': '5.71'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                       
+
+  6%|▌         | 6500/112100 [24:31<6:03:55,  4.84it/s]{'loss': '1.234', 'grad_norm': '1.368', 'learning_rate': '4.71e-05', 'epoch': '5.799'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
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+                                                       
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.233', 'grad_norm': '1.53', 'learning_rate': '4.706e-05', 'epoch': '5.888'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
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+                                                       
+
+  6%|▌         | 6700/112100 [25:19<6:16:09,  4.67it/s]{'loss': '1.232', 'grad_norm': '1.278', 'learning_rate': '4.701e-05', 'epoch': '5.977'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
+  6%|▌         | 6727/112100 [25:30<26:06:52,  1.12it/s]
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+                                                       
+
+  6%|▌         | 6800/112100 [25:46<5:27:41,  5.36it/s]{'loss': '1.231', 'grad_norm': '1.188', 'learning_rate': '4.697e-05', 'epoch': '6.066'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                       
+
+  6%|▌         | 6900/112100 [26:10<6:56:28,  4.21it/s]{'loss': '1.233', 'grad_norm': '1.352', 'learning_rate': '4.692e-05', 'epoch': '6.155'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+
+  6%|▌         | 6901/112100 [26:12<26:32:52,  1.10it/s]
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+                                                       
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.231', 'grad_norm': '1.633', 'learning_rate': '4.688e-05', 'epoch': '6.245'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
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+                                                       
+
+  6%|▋         | 7100/112100 [26:58<6:25:02,  4.54it/s]{'loss': '1.231', 'grad_norm': '1.78', 'learning_rate': '4.683e-05', 'epoch': '6.334'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+  6%|▋         | 7197/112100 [27:21<6:25:28,  4.54it/s]
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+                                                       
+
+  6%|▋         | 7200/112100 [27:21<6:33:53,  4.44it/s]{'loss': '1.233', 'grad_norm': '0.9935', 'learning_rate': '4.679e-05', 'epoch': '6.423'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+
+  6%|▋         | 7201/112100 [27:24<23:55:08,  1.22it/s]
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+  6%|▋         | 7219/112100 [27:27<6:26:37,  4.52it/s]
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+  6%|▋         | 7221/112100 [27:28<6:41:11,  4.36it/s]
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+  6%|▋         | 7233/112100 [27:31<6:49:25,  4.27it/s]
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+  6%|▋         | 7246/112100 [27:34<6:37:19,  4.40it/s]
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+  6%|▋         | 7249/112100 [27:34<6:30:24,  4.48it/s]
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+  6%|▋         | 7251/112100 [27:35<6:40:02,  4.37it/s]
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+  6%|▋         | 7256/112100 [27:36<7:03:06,  4.13it/s]
+  6%|▋         | 7257/112100 [27:36<6:59:43,  4.16it/s]
+  6%|▋         | 7258/112100 [27:37<7:01:38,  4.14it/s]
+  6%|▋         | 7259/112100 [27:37<7:02:27,  4.14it/s]
+  6%|▋         | 7260/112100 [27:37<7:07:56,  4.08it/s]
+  6%|▋         | 7261/112100 [27:37<7:03:26,  4.13it/s]
+  6%|▋         | 7262/112100 [27:38<7:03:47,  4.12it/s]
+  6%|▋         | 7263/112100 [27:38<7:06:05,  4.10it/s]
+  6%|▋         | 7264/112100 [27:38<7:03:14,  4.13it/s]
+  6%|▋         | 7265/112100 [27:38<7:01:34,  4.14it/s]
+  6%|▋         | 7266/112100 [27:38<6:55:43,  4.20it/s]
+  6%|▋         | 7267/112100 [27:39<7:06:57,  4.09it/s]
+  6%|▋         | 7268/112100 [27:39<6:47:27,  4.29it/s]
+  6%|▋         | 7269/112100 [27:39<7:03:11,  4.13it/s]
+  6%|▋         | 7270/112100 [27:39<7:10:27,  4.06it/s]
+  6%|▋         | 7271/112100 [27:40<6:53:12,  4.23it/s]
+  6%|▋         | 7272/112100 [27:40<6:47:07,  4.29it/s]
+  6%|▋         | 7273/112100 [27:40<6:43:18,  4.33it/s]
+  6%|▋         | 7274/112100 [27:40<6:23:46,  4.55it/s]
+  6%|▋         | 7275/112100 [27:41<6:32:08,  4.46it/s]
+  6%|▋         | 7276/112100 [27:41<6:37:44,  4.39it/s]
+  6%|▋         | 7277/112100 [27:41<6:49:04,  4.27it/s]
+  6%|▋         | 7278/112100 [27:41<6:52:12,  4.24it/s]
+  6%|▋         | 7279/112100 [27:42<6:59:51,  4.16it/s]
+  6%|▋         | 7280/112100 [27:42<6:56:47,  4.19it/s]
+  6%|▋         | 7281/112100 [27:42<7:03:37,  4.12it/s]
+  6%|▋         | 7282/112100 [27:42<7:02:21,  4.14it/s]
+  6%|▋         | 7283/112100 [27:42<7:07:47,  4.08it/s]
+  6%|▋         | 7284/112100 [27:43<7:05:32,  4.11it/s]
+  6%|▋         | 7285/112100 [27:43<7:01:10,  4.15it/s]
+  6%|▋         | 7286/112100 [27:43<6:50:48,  4.25it/s]
+  7%|▋         | 7287/112100 [27:43<6:45:30,  4.31it/s]
+  7%|▋         | 7288/112100 [27:44<6:35:54,  4.41it/s]
+  7%|▋         | 7289/112100 [27:44<6:30:44,  4.47it/s]
+  7%|▋         | 7290/112100 [27:44<6:32:33,  4.45it/s]
+  7%|▋         | 7291/112100 [27:44<6:34:51,  4.42it/s]
+  7%|▋         | 7292/112100 [27:45<6:31:08,  4.47it/s]
+  7%|▋         | 7293/112100 [27:45<6:25:23,  4.53it/s]
+  7%|▋         | 7294/112100 [27:45<6:31:17,  4.46it/s]
+  7%|▋         | 7295/112100 [27:45<6:37:19,  4.40it/s]
+  7%|▋         | 7296/112100 [27:45<6:39:59,  4.37it/s]
+  7%|▋         | 7297/112100 [27:46<6:46:47,  4.29it/s]
+  7%|▋         | 7298/112100 [27:46<6:47:38,  4.28it/s]
+  7%|▋         | 7299/112100 [27:46<6:49:47,  4.26it/s]
+  7%|▋         | 7300/112100 [27:46<6:52:52,  4.23it/s]
+                                                       
+
+  7%|▋         | 7300/112100 [27:46<6:52:52,  4.23it/s]{'loss': '1.231', 'grad_norm': '1.255', 'learning_rate': '4.674e-05', 'epoch': '6.512'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+
+  7%|▋         | 7301/112100 [27:49<24:36:44,  1.18it/s]
+  7%|▋         | 7302/112100 [27:49<19:18:19,  1.51it/s]
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+  7%|▋         | 7304/112100 [27:49<12:58:48,  2.24it/s]
+  7%|▋         | 7305/112100 [27:50<11:05:36,  2.62it/s]
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+  7%|▋         | 7307/112100 [27:50<8:48:47,  3.30it/s]
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+  7%|▋         | 7309/112100 [27:50<7:17:58,  3.99it/s]
+  7%|▋         | 7310/112100 [27:51<6:49:48,  4.26it/s]
+  7%|▋         | 7311/112100 [27:51<6:31:58,  4.46it/s]
+  7%|▋         | 7312/112100 [27:51<6:14:47,  4.66it/s]
+  7%|▋         | 7313/112100 [27:51<5:59:24,  4.86it/s]
+  7%|▋         | 7314/112100 [27:51<5:46:26,  5.04it/s]
+  7%|▋         | 7315/112100 [27:52<5:39:14,  5.15it/s]
+  7%|▋         | 7316/112100 [27:52<5:33:48,  5.23it/s]
+  7%|▋         | 7317/112100 [27:52<5:29:57,  5.29it/s]
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+  7%|▋         | 7319/112100 [27:52<5:26:27,  5.35it/s]
+  7%|▋         | 7320/112100 [27:53<5:24:19,  5.38it/s]
+  7%|▋         | 7321/112100 [27:53<5:24:01,  5.39it/s]
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+  7%|▋         | 7323/112100 [27:53<5:24:12,  5.39it/s]
+  7%|▋         | 7324/112100 [27:53<5:26:53,  5.34it/s]
+  7%|▋         | 7325/112100 [27:53<5:30:43,  5.28it/s]
+  7%|▋         | 7326/112100 [27:54<5:31:36,  5.27it/s]
+  7%|▋         | 7327/112100 [27:54<5:35:55,  5.20it/s]
+  7%|▋         | 7328/112100 [27:54<5:39:01,  5.15it/s]
+  7%|▋         | 7329/112100 [27:54<5:38:38,  5.16it/s]
+  7%|▋         | 7330/112100 [27:54<5:39:47,  5.14it/s]
+  7%|▋         | 7331/112100 [27:55<5:44:33,  5.07it/s]
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+  7%|▋         | 7333/112100 [27:55<5:48:59,  5.00it/s]
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+  7%|▋         | 7341/112100 [27:57<5:57:08,  4.89it/s]
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+  7%|▋         | 7350/112100 [27:58<5:44:03,  5.07it/s]
+  7%|▋         | 7351/112100 [27:59<5:44:25,  5.07it/s]
+  7%|▋         | 7352/112100 [27:59<5:43:18,  5.09it/s]
+  7%|▋         | 7353/112100 [27:59<5:44:30,  5.07it/s]
+  7%|▋         | 7354/112100 [27:59<5:42:01,  5.10it/s]
+  7%|▋         | 7355/112100 [27:59<5:41:25,  5.11it/s]
+  7%|▋         | 7356/112100 [28:00<5:36:45,  5.18it/s]
+  7%|▋         | 7357/112100 [28:00<5:28:26,  5.32it/s]
+  7%|▋         | 7358/112100 [28:00<5:22:32,  5.41it/s]
+  7%|▋         | 7359/112100 [28:00<5:22:25,  5.41it/s]
+  7%|▋         | 7360/112100 [28:00<5:21:12,  5.43it/s]
+  7%|▋         | 7361/112100 [28:00<5:18:50,  5.48it/s]
+  7%|▋         | 7362/112100 [28:01<5:16:27,  5.52it/s]
+  7%|▋         | 7363/112100 [28:01<5:18:47,  5.48it/s]
+  7%|▋         | 7364/112100 [28:01<5:18:30,  5.48it/s]
+  7%|▋         | 7365/112100 [28:01<5:19:02,  5.47it/s]
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+  7%|▋         | 7367/112100 [28:02<5:17:44,  5.49it/s]
+  7%|▋         | 7368/112100 [28:02<5:16:07,  5.52it/s]
+  7%|▋         | 7369/112100 [28:02<5:14:35,  5.55it/s]
+  7%|▋         | 7370/112100 [28:02<5:12:58,  5.58it/s]
+  7%|▋         | 7371/112100 [28:02<5:19:43,  5.46it/s]
+  7%|▋         | 7372/112100 [28:03<5:24:03,  5.39it/s]
+  7%|▋         | 7373/112100 [28:03<5:26:19,  5.35it/s]
+  7%|▋         | 7374/112100 [28:03<5:40:19,  5.13it/s]
+  7%|▋         | 7375/112100 [28:03<6:05:09,  4.78it/s]
+  7%|▋         | 7376/112100 [28:03<6:15:19,  4.65it/s]
+  7%|▋         | 7377/112100 [28:04<6:27:50,  4.50it/s]
+  7%|▋         | 7378/112100 [28:04<6:37:09,  4.39it/s]
+  7%|▋         | 7379/112100 [28:04<6:42:24,  4.34it/s]
+  7%|▋         | 7380/112100 [28:04<6:41:19,  4.35it/s]
+  7%|▋         | 7381/112100 [28:05<6:45:33,  4.30it/s]
+  7%|▋         | 7382/112100 [28:05<6:51:36,  4.24it/s]
+  7%|▋         | 7383/112100 [28:05<6:49:19,  4.26it/s]
+  7%|▋         | 7384/112100 [28:05<6:49:07,  4.27it/s]
+  7%|▋         | 7385/112100 [28:06<6:52:45,  4.23it/s]
+  7%|▋         | 7386/112100 [28:06<6:48:32,  4.27it/s]
+  7%|▋         | 7387/112100 [28:06<6:36:36,  4.40it/s]
+  7%|▋         | 7388/112100 [28:06<6:27:04,  4.51it/s]
+  7%|▋         | 7389/112100 [28:06<6:41:30,  4.35it/s]
+  7%|▋         | 7390/112100 [28:07<6:38:02,  4.38it/s]
+  7%|▋         | 7391/112100 [28:07<6:28:29,  4.49it/s]
+  7%|▋         | 7392/112100 [28:07<6:28:19,  4.49it/s]
+  7%|▋         | 7393/112100 [28:07<6:26:36,  4.51it/s]
+  7%|▋         | 7394/112100 [28:08<6:27:51,  4.50it/s]
+  7%|▋         | 7395/112100 [28:08<6:37:21,  4.39it/s]
+  7%|▋         | 7396/112100 [28:08<6:43:46,  4.32it/s]
+  7%|▋         | 7397/112100 [28:08<6:52:43,  4.23it/s]
+  7%|▋         | 7398/112100 [28:08<6:57:07,  4.18it/s]
+  7%|▋         | 7399/112100 [28:09<6:59:36,  4.16it/s]
+  7%|▋         | 7400/112100 [28:09<7:00:49,  4.15it/s]
+                                                       
+
+  7%|▋         | 7400/112100 [28:09<7:00:49,  4.15it/s]{'loss': '1.23', 'grad_norm': '1.152', 'learning_rate': '4.67e-05', 'epoch': '6.602'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
+
+  7%|▋         | 7401/112100 [28:11<26:47:18,  1.09it/s]
+  7%|▋         | 7402/112100 [28:12<20:45:05,  1.40it/s]
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+  7%|▋         | 7404/112100 [28:12<13:48:06,  2.11it/s]
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+  7%|▋         | 7406/112100 [28:13<10:02:00,  2.90it/s]
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+  7%|▋         | 7408/112100 [28:13<8:21:35,  3.48it/s]
+  7%|▋         | 7409/112100 [28:13<8:00:51,  3.63it/s]
+  7%|▋         | 7410/112100 [28:14<7:40:05,  3.79it/s]
+  7%|▋         | 7411/112100 [28:14<7:30:16,  3.87it/s]
+  7%|▋         | 7412/112100 [28:14<7:25:19,  3.92it/s]
+  7%|▋         | 7413/112100 [28:14<7:17:16,  3.99it/s]
+  7%|▋         | 7414/112100 [28:15<7:09:03,  4.07it/s]
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+  7%|▋         | 7416/112100 [28:15<6:55:07,  4.20it/s]
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+  7%|▋         | 7419/112100 [28:16<6:48:52,  4.27it/s]
+  7%|▋         | 7420/112100 [28:16<6:42:29,  4.33it/s]
+  7%|▋         | 7421/112100 [28:16<6:46:49,  4.29it/s]
+  7%|▋         | 7422/112100 [28:16<6:48:38,  4.27it/s]
+  7%|▋         | 7423/112100 [28:17<6:45:43,  4.30it/s]
+  7%|▋         | 7424/112100 [28:17<6:46:38,  4.29it/s]
+  7%|▋         | 7425/112100 [28:17<6:50:34,  4.25it/s]
+  7%|▋         | 7426/112100 [28:17<6:54:25,  4.21it/s]
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+  7%|▋         | 7429/112100 [28:18<6:59:21,  4.16it/s]
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+  7%|▋         | 7460/112100 [28:25<6:29:10,  4.48it/s]
+  7%|▋         | 7461/112100 [28:25<6:27:40,  4.50it/s]
+  7%|▋         | 7462/112100 [28:26<6:41:43,  4.34it/s]
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+  7%|▋         | 7475/112100 [28:29<7:01:39,  4.14it/s]
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+  7%|▋         | 7478/112100 [28:29<7:02:43,  4.12it/s]
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+  7%|▋         | 7480/112100 [28:30<7:02:49,  4.12it/s]
+  7%|▋         | 7481/112100 [28:30<7:03:17,  4.12it/s]
+  7%|▋         | 7482/112100 [28:30<7:01:23,  4.14it/s]
+  7%|▋         | 7483/112100 [28:31<7:05:50,  4.09it/s]
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+  7%|▋         | 7487/112100 [28:32<6:35:14,  4.41it/s]
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+  7%|▋         | 7489/112100 [28:32<6:28:33,  4.49it/s]
+  7%|▋         | 7490/112100 [28:32<6:25:27,  4.52it/s]
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+  7%|▋         | 7492/112100 [28:33<6:26:12,  4.51it/s]
+  7%|▋         | 7493/112100 [28:33<6:35:28,  4.41it/s]
+  7%|▋         | 7494/112100 [28:33<6:32:27,  4.44it/s]
+  7%|▋         | 7495/112100 [28:33<6:38:10,  4.38it/s]
+  7%|▋         | 7496/112100 [28:34<6:37:58,  4.38it/s]
+  7%|▋         | 7497/112100 [28:34<6:32:10,  4.45it/s]
+  7%|▋         | 7498/112100 [28:34<6:25:00,  4.53it/s]
+  7%|▋         | 7499/112100 [28:34<6:23:48,  4.54it/s]
+  7%|▋         | 7500/112100 [28:34<6:20:33,  4.58it/s]
+                                                       
+
+  7%|▋         | 7500/112100 [28:34<6:20:33,  4.58it/s]{'loss': '1.23', 'grad_norm': '1.261', 'learning_rate': '4.666e-05', 'epoch': '6.691'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+
+  7%|▋         | 7501/112100 [28:37<26:03:27,  1.12it/s]
+  7%|▋         | 7502/112100 [28:37<19:51:25,  1.46it/s]
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+  7%|▋         | 7504/112100 [28:37<12:29:33,  2.33it/s]
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+  7%|▋         | 7507/112100 [28:38<7:58:08,  3.65it/s]
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+  7%|▋         | 7509/112100 [28:38<7:03:11,  4.12it/s]
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+  7%|▋         | 7540/112100 [28:44<5:25:24,  5.36it/s]
+  7%|▋         | 7541/112100 [28:45<5:23:24,  5.39it/s]
+  7%|▋         | 7542/112100 [28:45<5:26:18,  5.34it/s]
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+  7%|▋         | 7551/112100 [28:47<5:29:30,  5.29it/s]
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+  7%|▋         | 7554/112100 [28:47<5:36:36,  5.18it/s]
+  7%|▋         | 7555/112100 [28:47<5:43:26,  5.07it/s]
+  7%|▋         | 7556/112100 [28:48<5:48:41,  5.00it/s]
+  7%|▋         | 7557/112100 [28:48<5:53:54,  4.92it/s]
+  7%|▋         | 7558/112100 [28:48<5:56:23,  4.89it/s]
+  7%|▋         | 7559/112100 [28:48<6:01:33,  4.82it/s]
+  7%|▋         | 7560/112100 [28:48<6:00:54,  4.83it/s]
+  7%|▋         | 7561/112100 [28:49<6:03:18,  4.80it/s]
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+  7%|▋         | 7563/112100 [28:49<6:13:20,  4.67it/s]
+  7%|▋         | 7564/112100 [28:49<6:21:28,  4.57it/s]
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+  7%|▋         | 7566/112100 [28:50<6:32:19,  4.44it/s]
+  7%|▋         | 7567/112100 [28:50<6:36:56,  4.39it/s]
+  7%|▋         | 7568/112100 [28:50<6:42:03,  4.33it/s]
+  7%|▋         | 7569/112100 [28:50<6:47:28,  4.28it/s]
+  7%|▋         | 7570/112100 [28:51<6:48:17,  4.27it/s]
+  7%|▋         | 7571/112100 [28:51<6:51:47,  4.23it/s]
+  7%|▋         | 7572/112100 [28:51<6:58:24,  4.16it/s]
+  7%|▋         | 7573/112100 [28:51<6:57:40,  4.17it/s]
+  7%|▋         | 7574/112100 [28:52<7:03:00,  4.12it/s]
+  7%|▋         | 7575/112100 [28:52<7:05:01,  4.10it/s]
+  7%|▋         | 7576/112100 [28:52<7:05:00,  4.10it/s]
+  7%|▋         | 7577/112100 [28:52<7:03:46,  4.11it/s]
+  7%|▋         | 7578/112100 [28:53<7:04:11,  4.11it/s]
+  7%|▋         | 7579/112100 [28:53<7:04:53,  4.10it/s]
+  7%|▋         | 7580/112100 [28:53<7:04:15,  4.11it/s]
+  7%|▋         | 7581/112100 [28:53<6:59:06,  4.16it/s]
+  7%|▋         | 7582/112100 [28:54<6:57:10,  4.18it/s]
+  7%|▋         | 7583/112100 [28:54<6:46:50,  4.28it/s]
+  7%|▋         | 7584/112100 [28:54<6:38:52,  4.37it/s]
+  7%|▋         | 7585/112100 [28:54<6:35:14,  4.41it/s]
+  7%|▋         | 7586/112100 [28:54<6:34:01,  4.42it/s]
+  7%|▋         | 7587/112100 [28:55<6:34:53,  4.41it/s]
+  7%|▋         | 7588/112100 [28:55<6:30:15,  4.46it/s]
+  7%|▋         | 7589/112100 [28:55<6:25:21,  4.52it/s]
+  7%|▋         | 7590/112100 [28:55<6:33:04,  4.43it/s]
+  7%|▋         | 7591/112100 [28:56<6:32:41,  4.44it/s]
+  7%|▋         | 7592/112100 [28:56<6:36:42,  4.39it/s]
+  7%|▋         | 7593/112100 [28:56<6:44:24,  4.31it/s]
+  7%|▋         | 7594/112100 [28:56<6:42:50,  4.32it/s]
+  7%|▋         | 7595/112100 [28:57<6:48:17,  4.27it/s]
+  7%|▋         | 7596/112100 [28:57<6:53:56,  4.21it/s]
+  7%|▋         | 7597/112100 [28:57<7:02:00,  4.13it/s]
+  7%|▋         | 7598/112100 [28:57<7:00:26,  4.14it/s]
+  7%|▋         | 7599/112100 [28:58<6:58:50,  4.16it/s]
+  7%|▋         | 7600/112100 [28:58<7:01:13,  4.13it/s]
+                                                       
+
+  7%|▋         | 7600/112100 [28:58<7:01:13,  4.13it/s]{'loss': '1.232', 'grad_norm': '1.355', 'learning_rate': '4.661e-05', 'epoch': '6.78'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+
+  7%|▋         | 7601/112100 [29:00<26:18:00,  1.10it/s]
+  7%|▋         | 7602/112100 [29:00<20:31:34,  1.41it/s]
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+  7%|▋         | 7604/112100 [29:01<13:23:17,  2.17it/s]
+  7%|▋         | 7605/112100 [29:01<11:11:43,  2.59it/s]
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+  7%|▋         | 7607/112100 [29:02<8:46:18,  3.31it/s]
+  7%|▋         | 7608/112100 [29:02<8:10:41,  3.55it/s]
+  7%|▋         | 7609/112100 [29:02<7:40:57,  3.78it/s]
+  7%|▋         | 7610/112100 [29:02<7:24:16,  3.92it/s]
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+  7%|▋         | 7612/112100 [29:03<7:10:59,  4.04it/s]
+  7%|▋         | 7613/112100 [29:03<7:05:42,  4.09it/s]
+  7%|▋         | 7614/112100 [29:03<7:05:28,  4.09it/s]
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+  7%|▋         | 7616/112100 [29:04<7:02:41,  4.12it/s]
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+  7%|▋         | 7619/112100 [29:04<6:46:14,  4.29it/s]
+  7%|▋         | 7620/112100 [29:05<6:47:28,  4.27it/s]
+  7%|▋         | 7621/112100 [29:05<6:41:10,  4.34it/s]
+  7%|▋         | 7622/112100 [29:05<6:43:17,  4.32it/s]
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+  7%|▋         | 7624/112100 [29:06<6:45:16,  4.30it/s]
+  7%|▋         | 7625/112100 [29:06<6:38:40,  4.37it/s]
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+  7%|▋         | 7628/112100 [29:07<6:54:23,  4.20it/s]
+  7%|▋         | 7629/112100 [29:07<6:56:53,  4.18it/s]
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+  7%|▋         | 7631/112100 [29:07<6:57:23,  4.17it/s]
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+  7%|▋         | 7633/112100 [29:08<7:03:38,  4.11it/s]
+  7%|▋         | 7634/112100 [29:08<7:01:22,  4.13it/s]
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+  7%|▋         | 7641/112100 [29:10<7:03:42,  4.11it/s]
+  7%|▋         | 7642/112100 [29:10<7:03:30,  4.11it/s]
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+  7%|▋         | 7646/112100 [29:11<7:07:33,  4.07it/s]
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+                                                       
+
+  7%|▋         | 7700/112100 [29:22<6:09:05,  4.71it/s]{'loss': '1.232', 'grad_norm': '1.315', 'learning_rate': '4.657e-05', 'epoch': '6.869'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+  7%|▋         | 7796/112100 [29:46<6:56:46,  4.17it/s]
+  7%|▋         | 7797/112100 [29:46<6:51:39,  4.22it/s]
+  7%|▋         | 7798/112100 [29:46<6:50:12,  4.24it/s]
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+  7%|▋         | 7800/112100 [29:46<7:05:23,  4.09it/s]
+                                                       
+
+  7%|▋         | 7800/112100 [29:47<7:05:23,  4.09it/s]{'loss': '1.23', 'grad_norm': '1.742', 'learning_rate': '4.652e-05', 'epoch': '6.959'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+  7%|▋         | 7801/112100 [29:49<22:37:20,  1.28it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.42it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.42it/s]
+
+  7%|▋         | 7848/112100 [30:01<22:42:12,  1.28it/s]
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+  7%|▋         | 7900/112100 [30:11<5:44:19,  5.04it/s]
+                                                       
+
+  7%|▋         | 7900/112100 [30:11<5:44:19,  5.04it/s]{'loss': '1.229', 'grad_norm': '1.727', 'learning_rate': '4.648e-05', 'epoch': '7.047'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+  7%|▋         | 7997/112100 [30:35<5:56:37,  4.87it/s]
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+  7%|▋         | 8000/112100 [30:36<6:11:30,  4.67it/s]
+                                                       
+
+  7%|▋         | 8000/112100 [30:36<6:11:30,  4.67it/s]{'loss': '1.23', 'grad_norm': '1.519', 'learning_rate': '4.643e-05', 'epoch': '7.137'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
+  7%|▋         | 8001/112100 [30:39<25:39:48,  1.13it/s]
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+                                                       
+
+  7%|▋         | 8100/112100 [30:59<6:14:30,  4.63it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.23', 'grad_norm': '1.403', 'learning_rate': '4.639e-05', 'epoch': '7.226'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+  7%|▋         | 8195/112100 [31:24<6:36:21,  4.37it/s]
+  7%|▋         | 8196/112100 [31:24<6:30:34,  4.43it/s]
+  7%|▋         | 8197/112100 [31:24<6:30:09,  4.44it/s]
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+  7%|▋         | 8200/112100 [31:25<6:20:17,  4.55it/s]
+                                                       
+
+  7%|▋         | 8200/112100 [31:25<6:20:17,  4.55it/s]{'loss': '1.229', 'grad_norm': '1.465', 'learning_rate': '4.634e-05', 'epoch': '7.315'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+
+  7%|▋         | 8201/112100 [31:27<25:00:27,  1.15it/s]
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+  7%|▋         | 8207/112100 [31:28<7:45:24,  3.72it/s]
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+  7%|▋         | 8263/112100 [31:40<6:22:23,  4.53it/s]
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+  7%|▋         | 8277/112100 [31:43<6:12:14,  4.65it/s]
+  7%|▋         | 8278/112100 [31:43<6:21:13,  4.54it/s]
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+  7%|▋         | 8280/112100 [31:43<6:21:48,  4.53it/s]
+  7%|▋         | 8281/112100 [31:44<6:21:14,  4.54it/s]
+  7%|▋         | 8282/112100 [31:44<6:27:15,  4.47it/s]
+  7%|▋         | 8283/112100 [31:44<6:34:38,  4.38it/s]
+  7%|▋         | 8284/112100 [31:44<6:31:05,  4.42it/s]
+  7%|▋         | 8285/112100 [31:44<6:29:20,  4.44it/s]
+  7%|▋         | 8286/112100 [31:45<6:27:21,  4.47it/s]
+  7%|▋         | 8287/112100 [31:45<6:22:33,  4.52it/s]
+  7%|▋         | 8288/112100 [31:45<6:15:05,  4.61it/s]
+  7%|▋         | 8289/112100 [31:45<6:12:03,  4.65it/s]
+  7%|▋         | 8290/112100 [31:46<6:16:30,  4.60it/s]
+  7%|▋         | 8291/112100 [31:46<6:20:25,  4.55it/s]
+  7%|▋         | 8292/112100 [31:46<6:19:54,  4.55it/s]
+  7%|▋         | 8293/112100 [31:46<6:24:17,  4.50it/s]
+  7%|▋         | 8294/112100 [31:46<6:29:57,  4.44it/s]
+  7%|▋         | 8295/112100 [31:47<6:33:29,  4.40it/s]
+  7%|▋         | 8296/112100 [31:47<6:39:42,  4.33it/s]
+  7%|▋         | 8297/112100 [31:47<6:45:00,  4.27it/s]
+  7%|▋         | 8298/112100 [31:47<6:42:32,  4.30it/s]
+  7%|▋         | 8299/112100 [31:48<6:38:56,  4.34it/s]
+  7%|▋         | 8300/112100 [31:48<6:33:21,  4.40it/s]
+                                                       
+
+  7%|▋         | 8300/112100 [31:48<6:33:21,  4.40it/s]{'loss': '1.231', 'grad_norm': '1.245', 'learning_rate': '4.63e-05', 'epoch': '7.404'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+
+  7%|▋         | 8301/112100 [31:50<25:21:35,  1.14it/s]
+  7%|▋         | 8302/112100 [31:50<19:48:15,  1.46it/s]
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+  7%|▋         | 8314/112100 [31:53<6:55:09,  4.17it/s]
+  7%|▋         | 8315/112100 [31:54<6:48:22,  4.24it/s]
+  7%|▋         | 8316/112100 [31:54<6:40:46,  4.32it/s]
+  7%|▋         | 8317/112100 [31:54<6:34:10,  4.39it/s]
+  7%|▋         | 8318/112100 [31:54<6:30:37,  4.43it/s]
+  7%|▋         | 8319/112100 [31:54<6:30:30,  4.43it/s]
+  7%|▋         | 8320/112100 [31:55<6:38:10,  4.34it/s]
+  7%|▋         | 8321/112100 [31:55<6:40:08,  4.32it/s]
+  7%|▋         | 8322/112100 [31:55<6:37:14,  4.35it/s]
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+  7%|▋         | 8324/112100 [31:56<6:40:05,  4.32it/s]
+  7%|▋         | 8325/112100 [31:56<6:38:35,  4.34it/s]
+  7%|▋         | 8326/112100 [31:56<6:44:37,  4.27it/s]
+  7%|▋         | 8327/112100 [31:56<6:34:58,  4.38it/s]
+  7%|▋         | 8328/112100 [31:57<6:37:23,  4.35it/s]
+  7%|▋         | 8329/112100 [31:57<6:39:51,  4.33it/s]
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+  7%|▋         | 8331/112100 [31:57<6:43:34,  4.29it/s]
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+  7%|▋         | 8333/112100 [31:58<6:28:20,  4.45it/s]
+  7%|▋         | 8334/112100 [31:58<6:26:55,  4.47it/s]
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+  7%|▋         | 8339/112100 [31:59<6:33:02,  4.40it/s]
+  7%|▋         | 8340/112100 [31:59<6:36:39,  4.36it/s]
+  7%|▋         | 8341/112100 [31:59<6:37:09,  4.35it/s]
+  7%|▋         | 8342/112100 [32:00<6:29:39,  4.44it/s]
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+  7%|▋         | 8350/112100 [32:02<6:45:32,  4.26it/s]
+  7%|▋         | 8351/112100 [32:02<6:47:06,  4.25it/s]
+  7%|▋         | 8352/112100 [32:02<6:49:22,  4.22it/s]
+  7%|▋         | 8353/112100 [32:02<6:54:41,  4.17it/s]
+  7%|▋         | 8354/112100 [32:03<6:51:57,  4.20it/s]
+  7%|▋         | 8355/112100 [32:03<6:51:53,  4.20it/s]
+  7%|▋         | 8356/112100 [32:03<6:54:30,  4.17it/s]
+  7%|▋         | 8357/112100 [32:03<6:59:10,  4.12it/s]
+  7%|▋         | 8358/112100 [32:03<6:59:29,  4.12it/s]
+  7%|▋         | 8359/112100 [32:04<6:57:56,  4.14it/s]
+  7%|▋         | 8360/112100 [32:04<6:59:43,  4.12it/s]
+  7%|▋         | 8361/112100 [32:04<7:04:50,  4.07it/s]
+  7%|▋         | 8362/112100 [32:04<7:02:38,  4.09it/s]
+  7%|▋         | 8363/112100 [32:05<7:03:42,  4.08it/s]
+  7%|▋         | 8364/112100 [32:05<6:59:46,  4.12it/s]
+  7%|▋         | 8365/112100 [32:05<6:58:54,  4.13it/s]
+  7%|▋         | 8366/112100 [32:05<6:58:26,  4.13it/s]
+  7%|▋         | 8367/112100 [32:06<6:53:37,  4.18it/s]
+  7%|▋         | 8368/112100 [32:06<6:57:21,  4.14it/s]
+  7%|▋         | 8369/112100 [32:06<6:49:39,  4.22it/s]
+  7%|▋         | 8370/112100 [32:06<6:43:54,  4.28it/s]
+  7%|▋         | 8371/112100 [32:07<6:34:20,  4.38it/s]
+  7%|▋         | 8372/112100 [32:07<6:28:32,  4.45it/s]
+  7%|▋         | 8373/112100 [32:07<6:29:27,  4.44it/s]
+  7%|▋         | 8374/112100 [32:07<6:27:24,  4.46it/s]
+  7%|▋         | 8375/112100 [32:07<6:28:42,  4.45it/s]
+  7%|▋         | 8376/112100 [32:08<6:27:12,  4.46it/s]
+  7%|▋         | 8377/112100 [32:08<6:13:57,  4.62it/s]
+  7%|▋         | 8378/112100 [32:08<6:05:06,  4.73it/s]
+  7%|▋         | 8379/112100 [32:08<5:58:53,  4.82it/s]
+  7%|▋         | 8380/112100 [32:08<5:59:23,  4.81it/s]
+  7%|▋         | 8381/112100 [32:09<5:50:11,  4.94it/s]
+  7%|▋         | 8382/112100 [32:09<5:47:25,  4.98it/s]
+  7%|▋         | 8383/112100 [32:09<5:44:42,  5.01it/s]
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+  7%|▋         | 8386/112100 [32:10<5:34:05,  5.17it/s]
+  7%|▋         | 8387/112100 [32:10<5:34:51,  5.16it/s]
+  7%|▋         | 8388/112100 [32:10<5:35:18,  5.16it/s]
+  7%|▋         | 8389/112100 [32:10<5:36:59,  5.13it/s]
+  7%|▋         | 8390/112100 [32:10<5:35:30,  5.15it/s]
+  7%|▋         | 8391/112100 [32:11<5:39:27,  5.09it/s]
+  7%|▋         | 8392/112100 [32:11<5:41:17,  5.06it/s]
+  7%|▋         | 8393/112100 [32:11<5:40:56,  5.07it/s]
+  7%|▋         | 8394/112100 [32:11<5:40:27,  5.08it/s]
+  7%|▋         | 8395/112100 [32:11<5:40:11,  5.08it/s]
+  7%|▋         | 8396/112100 [32:12<5:38:40,  5.10it/s]
+  7%|▋         | 8397/112100 [32:12<5:42:58,  5.04it/s]
+  7%|▋         | 8398/112100 [32:12<5:48:10,  4.96it/s]
+  7%|▋         | 8399/112100 [32:12<5:52:50,  4.90it/s]
+  7%|▋         | 8400/112100 [32:12<5:59:51,  4.80it/s]
+                                                       
+
+  7%|▋         | 8400/112100 [32:12<5:59:51,  4.80it/s]{'loss': '1.229', 'grad_norm': '1.231', 'learning_rate': '4.625e-05', 'epoch': '7.494'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
+
+  7%|▋         | 8401/112100 [32:15<24:11:14,  1.19it/s]
+  7%|▋         | 8402/112100 [32:15<18:33:47,  1.55it/s]
+  7%|▋         | 8403/112100 [32:15<14:38:07,  1.97it/s]
+  7%|▋         | 8404/112100 [32:15<11:52:49,  2.42it/s]
+  7%|▋         | 8405/112100 [32:16<9:54:16,  2.91it/s] 
+  7%|▋         | 8406/112100 [32:16<8:42:22,  3.31it/s]
+  7%|▋         | 8407/112100 [32:16<7:54:39,  3.64it/s]
+  8%|▊         | 8408/112100 [32:16<7:19:21,  3.93it/s]
+  8%|▊         | 8409/112100 [32:16<6:56:47,  4.15it/s]
+  8%|▊         | 8410/112100 [32:17<6:39:37,  4.32it/s]
+  8%|▊         | 8411/112100 [32:17<6:26:36,  4.47it/s]
+  8%|▊         | 8412/112100 [32:17<6:10:18,  4.67it/s]
+  8%|▊         | 8413/112100 [32:17<5:59:07,  4.81it/s]
+  8%|▊         | 8414/112100 [32:17<5:48:19,  4.96it/s]
+  8%|▊         | 8415/112100 [32:18<5:41:43,  5.06it/s]
+  8%|▊         | 8416/112100 [32:18<5:38:51,  5.10it/s]
+  8%|▊         | 8417/112100 [32:18<5:37:46,  5.12it/s]
+  8%|▊         | 8418/112100 [32:18<5:36:51,  5.13it/s]
+  8%|▊         | 8419/112100 [32:18<5:36:38,  5.13it/s]
+  8%|▊         | 8420/112100 [32:18<5:34:04,  5.17it/s]
+  8%|▊         | 8421/112100 [32:19<5:30:13,  5.23it/s]
+  8%|▊         | 8422/112100 [32:19<5:38:20,  5.11it/s]
+  8%|▊         | 8423/112100 [32:19<5:30:36,  5.23it/s]
+  8%|▊         | 8424/112100 [32:19<5:30:10,  5.23it/s]
+  8%|▊         | 8425/112100 [32:19<5:37:01,  5.13it/s]
+  8%|▊         | 8426/112100 [32:20<5:29:02,  5.25it/s]
+  8%|▊         | 8427/112100 [32:20<5:22:45,  5.35it/s]
+  8%|▊         | 8428/112100 [32:20<5:17:31,  5.44it/s]
+  8%|▊         | 8429/112100 [32:20<5:14:01,  5.50it/s]
+  8%|▊         | 8430/112100 [32:20<5:12:06,  5.54it/s]
+  8%|▊         | 8431/112100 [32:21<5:19:16,  5.41it/s]
+  8%|▊         | 8432/112100 [32:21<5:39:29,  5.09it/s]
+  8%|▊         | 8433/112100 [32:21<5:50:16,  4.93it/s]
+  8%|▊         | 8434/112100 [32:21<6:00:17,  4.80it/s]
+  8%|▊         | 8435/112100 [32:21<6:05:01,  4.73it/s]
+  8%|▊         | 8436/112100 [32:22<6:04:58,  4.73it/s]
+  8%|▊         | 8437/112100 [32:22<6:06:39,  4.71it/s]
+  8%|▊         | 8438/112100 [32:22<6:17:15,  4.58it/s]
+  8%|▊         | 8439/112100 [32:22<6:25:33,  4.48it/s]
+  8%|▊         | 8440/112100 [32:23<6:32:45,  4.40it/s]
+  8%|▊         | 8441/112100 [32:23<6:41:58,  4.30it/s]
+  8%|▊         | 8442/112100 [32:23<6:42:58,  4.29it/s]
+  8%|▊         | 8443/112100 [32:23<6:30:18,  4.43it/s]
+  8%|▊         | 8444/112100 [32:23<6:29:54,  4.43it/s]
+  8%|▊         | 8445/112100 [32:24<6:27:19,  4.46it/s]
+  8%|▊         | 8446/112100 [32:24<6:27:06,  4.46it/s]
+  8%|▊         | 8447/112100 [32:24<6:32:23,  4.40it/s]
+  8%|▊         | 8448/112100 [32:24<6:31:13,  4.42it/s]
+  8%|▊         | 8449/112100 [32:25<6:29:52,  4.43it/s]
+  8%|▊         | 8450/112100 [32:25<6:13:05,  4.63it/s]
+  8%|▊         | 8451/112100 [32:25<6:19:18,  4.55it/s]
+  8%|▊         | 8452/112100 [32:25<6:11:30,  4.65it/s]
+  8%|▊         | 8453/112100 [32:25<6:13:27,  4.63it/s]
+  8%|▊         | 8454/112100 [32:26<6:22:46,  4.51it/s]
+  8%|▊         | 8455/112100 [32:26<6:28:42,  4.44it/s]
+  8%|▊         | 8456/112100 [32:26<6:28:47,  4.44it/s]
+  8%|▊         | 8457/112100 [32:26<6:34:32,  4.38it/s]
+  8%|▊         | 8458/112100 [32:27<6:39:50,  4.32it/s]
+  8%|▊         | 8459/112100 [32:27<6:45:34,  4.26it/s]
+  8%|▊         | 8460/112100 [32:27<6:49:23,  4.22it/s]
+  8%|▊         | 8461/112100 [32:27<6:51:15,  4.20it/s]
+  8%|▊         | 8462/112100 [32:28<6:55:26,  4.16it/s]
+  8%|▊         | 8463/112100 [32:28<6:53:09,  4.18it/s]
+  8%|▊         | 8464/112100 [32:28<6:56:46,  4.14it/s]
+  8%|▊         | 8465/112100 [32:28<6:57:12,  4.14it/s]
+  8%|▊         | 8466/112100 [32:29<6:50:52,  4.20it/s]
+  8%|▊         | 8467/112100 [32:29<6:44:41,  4.27it/s]
+  8%|▊         | 8468/112100 [32:29<6:45:57,  4.25it/s]
+  8%|▊         | 8469/112100 [32:29<6:43:23,  4.28it/s]
+  8%|▊         | 8470/112100 [32:29<6:32:22,  4.40it/s]
+  8%|▊         | 8471/112100 [32:30<6:31:27,  4.41it/s]
+  8%|▊         | 8472/112100 [32:30<6:31:58,  4.41it/s]
+  8%|▊         | 8473/112100 [32:30<6:30:10,  4.43it/s]
+  8%|▊         | 8474/112100 [32:30<6:34:58,  4.37it/s]
+  8%|▊         | 8475/112100 [32:31<6:32:32,  4.40it/s]
+  8%|▊         | 8476/112100 [32:31<6:36:21,  4.36it/s]
+  8%|▊         | 8477/112100 [32:31<6:28:49,  4.44it/s]
+  8%|▊         | 8478/112100 [32:31<6:29:50,  4.43it/s]
+  8%|▊         | 8479/112100 [32:31<6:32:18,  4.40it/s]
+  8%|▊         | 8480/112100 [32:32<6:27:03,  4.46it/s]
+  8%|▊         | 8481/112100 [32:32<6:28:56,  4.44it/s]
+  8%|▊         | 8482/112100 [32:32<6:34:38,  4.38it/s]
+  8%|▊         | 8483/112100 [32:32<6:38:23,  4.33it/s]
+  8%|▊         | 8484/112100 [32:33<6:45:35,  4.26it/s]
+  8%|▊         | 8485/112100 [32:33<6:49:31,  4.22it/s]
+  8%|▊         | 8486/112100 [32:33<6:48:55,  4.22it/s]
+  8%|▊         | 8487/112100 [32:33<6:46:26,  4.25it/s]
+  8%|▊         | 8488/112100 [32:34<6:42:42,  4.29it/s]
+  8%|▊         | 8489/112100 [32:34<6:45:41,  4.26it/s]
+  8%|▊         | 8490/112100 [32:34<6:44:22,  4.27it/s]
+  8%|▊         | 8491/112100 [32:34<6:45:31,  4.26it/s]
+  8%|▊         | 8492/112100 [32:35<6:40:18,  4.31it/s]
+  8%|▊         | 8493/112100 [32:35<6:42:43,  4.29it/s]
+  8%|▊         | 8494/112100 [32:35<6:49:55,  4.21it/s]
+  8%|▊         | 8495/112100 [32:35<6:50:59,  4.20it/s]
+  8%|▊         | 8496/112100 [32:35<6:51:41,  4.19it/s]
+  8%|▊         | 8497/112100 [32:36<6:48:22,  4.23it/s]
+  8%|▊         | 8498/112100 [32:36<6:43:53,  4.28it/s]
+  8%|▊         | 8499/112100 [32:36<6:43:13,  4.28it/s]
+  8%|▊         | 8500/112100 [32:36<6:46:10,  4.25it/s]
+                                                       
+
+  8%|▊         | 8500/112100 [32:36<6:46:10,  4.25it/s]{'loss': '1.229', 'grad_norm': '1.241', 'learning_rate': '4.621e-05', 'epoch': '7.583'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
+  8%|▊         | 8501/112100 [32:39<25:40:01,  1.12it/s]
+  8%|▊         | 8502/112100 [32:39<19:57:01,  1.44it/s]
+  8%|▊         | 8503/112100 [32:39<15:57:50,  1.80it/s]
+  8%|▊         | 8504/112100 [32:40<13:10:03,  2.19it/s]
+  8%|▊         | 8505/112100 [32:40<11:05:16,  2.60it/s]
+  8%|▊         | 8506/112100 [32:40<9:44:09,  2.96it/s] 
+  8%|▊         | 8507/112100 [32:40<8:43:54,  3.30it/s]
+  8%|▊         | 8508/112100 [32:40<8:05:55,  3.55it/s]
+  8%|▊         | 8509/112100 [32:41<7:30:34,  3.83it/s]
+  8%|▊         | 8510/112100 [32:41<7:11:07,  4.00it/s]
+  8%|▊         | 8511/112100 [32:41<7:10:43,  4.01it/s]
+  8%|▊         | 8512/112100 [32:41<7:04:39,  4.07it/s]
+  8%|▊         | 8513/112100 [32:42<7:07:45,  4.04it/s]
+  8%|▊         | 8514/112100 [32:42<7:04:43,  4.06it/s]
+  8%|▊         | 8515/112100 [32:42<7:02:37,  4.08it/s]
+  8%|▊         | 8516/112100 [32:42<7:03:18,  4.08it/s]
+  8%|▊         | 8517/112100 [32:43<7:02:51,  4.08it/s]
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+  8%|▊         | 8519/112100 [32:43<6:57:54,  4.13it/s]
+  8%|▊         | 8520/112100 [32:43<6:52:28,  4.19it/s]
+  8%|▊         | 8521/112100 [32:44<6:49:47,  4.21it/s]
+  8%|▊         | 8522/112100 [32:44<6:44:52,  4.26it/s]
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+  8%|▊         | 8589/112100 [32:58<5:28:57,  5.24it/s]
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+  8%|▊         | 8592/112100 [32:58<5:32:30,  5.19it/s]
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+  8%|▊         | 8596/112100 [32:59<5:46:12,  4.98it/s]
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+  8%|▊         | 8599/112100 [33:00<5:40:41,  5.06it/s]
+  8%|▊         | 8600/112100 [33:00<5:39:49,  5.08it/s]
+                                                       
+
+  8%|▊         | 8600/112100 [33:00<5:39:49,  5.08it/s]{'loss': '1.228', 'grad_norm': '1.095', 'learning_rate': '4.617e-05', 'epoch': '7.672'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+
+  8%|▊         | 8601/112100 [33:02<24:41:02,  1.16it/s]
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+  8%|▊         | 8654/112100 [33:14<6:44:47,  4.26it/s]
+  8%|▊         | 8655/112100 [33:15<6:37:14,  4.34it/s]
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+  8%|▊         | 8679/112100 [33:20<6:35:59,  4.35it/s]
+  8%|▊         | 8680/112100 [33:20<6:38:20,  4.33it/s]
+  8%|▊         | 8681/112100 [33:20<6:45:12,  4.25it/s]
+  8%|▊         | 8682/112100 [33:21<6:45:51,  4.25it/s]
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+  8%|▊         | 8684/112100 [33:21<6:49:51,  4.21it/s]
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+  8%|▊         | 8687/112100 [33:22<6:53:08,  4.17it/s]
+  8%|▊         | 8688/112100 [33:22<6:46:22,  4.24it/s]
+  8%|▊         | 8689/112100 [33:22<6:51:45,  4.19it/s]
+  8%|▊         | 8690/112100 [33:23<6:51:11,  4.19it/s]
+  8%|▊         | 8691/112100 [33:23<6:53:44,  4.17it/s]
+  8%|▊         | 8692/112100 [33:23<6:44:56,  4.26it/s]
+  8%|▊         | 8693/112100 [33:23<6:51:31,  4.19it/s]
+  8%|▊         | 8694/112100 [33:24<6:52:55,  4.17it/s]
+  8%|▊         | 8695/112100 [33:24<6:49:59,  4.20it/s]
+  8%|▊         | 8696/112100 [33:24<6:48:54,  4.21it/s]
+  8%|▊         | 8697/112100 [33:24<6:47:52,  4.23it/s]
+  8%|▊         | 8698/112100 [33:25<6:48:51,  4.22it/s]
+  8%|▊         | 8699/112100 [33:25<6:52:28,  4.18it/s]
+  8%|▊         | 8700/112100 [33:25<6:48:51,  4.22it/s]
+                                                       
+
+  8%|▊         | 8700/112100 [33:25<6:48:51,  4.22it/s]{'loss': '1.23', 'grad_norm': '1.427', 'learning_rate': '4.612e-05', 'epoch': '7.761'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
+
+  8%|▊         | 8701/112100 [33:28<26:21:43,  1.09it/s]
+  8%|▊         | 8702/112100 [33:28<20:24:33,  1.41it/s]
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+  8%|▊         | 8704/112100 [33:28<13:26:22,  2.14it/s]
+  8%|▊         | 8705/112100 [33:28<11:20:29,  2.53it/s]
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+  8%|▊         | 8707/112100 [33:29<8:38:24,  3.32it/s]
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+  8%|▊         | 8709/112100 [33:29<7:32:08,  3.81it/s]
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+  8%|▊         | 8721/112100 [33:32<6:19:01,  4.55it/s]
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+  8%|▊         | 8724/112100 [33:33<6:40:53,  4.30it/s]
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+  8%|▊         | 8757/112100 [33:39<5:44:50,  4.99it/s]
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+  8%|▊         | 8759/112100 [33:40<5:41:05,  5.05it/s]
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+  8%|▊         | 8763/112100 [33:40<5:38:09,  5.09it/s]
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+  8%|▊         | 8794/112100 [33:47<6:29:55,  4.42it/s]
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+  8%|▊         | 8796/112100 [33:47<6:52:11,  4.18it/s]
+  8%|▊         | 8797/112100 [33:47<6:45:39,  4.24it/s]
+  8%|▊         | 8798/112100 [33:48<6:56:13,  4.14it/s]
+  8%|▊         | 8799/112100 [33:48<6:55:33,  4.14it/s]
+  8%|▊         | 8800/112100 [33:48<7:00:48,  4.09it/s]
+                                                       
+
+  8%|▊         | 8800/112100 [33:48<7:00:48,  4.09it/s]{'loss': '1.227', 'grad_norm': '1.506', 'learning_rate': '4.608e-05', 'epoch': '7.851'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+
+  8%|▊         | 8801/112100 [33:50<24:39:50,  1.16it/s]
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+  8%|▊         | 8853/112100 [34:02<6:29:38,  4.42it/s]
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+  8%|▊         | 8857/112100 [34:03<6:32:04,  4.39it/s]
+  8%|▊         | 8858/112100 [34:03<6:34:26,  4.36it/s]
+  8%|▊         | 8859/112100 [34:03<6:44:27,  4.25it/s]
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+  8%|▊         | 8863/112100 [34:04<6:53:36,  4.16it/s]
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+  8%|▊         | 8876/112100 [34:07<6:04:52,  4.71it/s]
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+  8%|▊         | 8878/112100 [34:08<6:07:48,  4.68it/s]
+  8%|▊         | 8879/112100 [34:08<6:08:34,  4.67it/s]
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+  8%|▊         | 8881/112100 [34:08<6:09:41,  4.65it/s]
+  8%|▊         | 8882/112100 [34:08<6:13:43,  4.60it/s]
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+  8%|▊         | 8887/112100 [34:10<6:25:14,  4.47it/s]
+  8%|▊         | 8888/112100 [34:10<6:29:05,  4.42it/s]
+  8%|▊         | 8889/112100 [34:10<6:26:54,  4.45it/s]
+  8%|▊         | 8890/112100 [34:10<6:27:48,  4.44it/s]
+  8%|▊         | 8891/112100 [34:10<6:29:34,  4.42it/s]
+  8%|▊         | 8892/112100 [34:11<6:38:45,  4.31it/s]
+  8%|▊         | 8893/112100 [34:11<6:43:20,  4.26it/s]
+  8%|▊         | 8894/112100 [34:11<6:43:08,  4.27it/s]
+  8%|▊         | 8895/112100 [34:11<6:51:51,  4.18it/s]
+  8%|▊         | 8896/112100 [34:12<6:49:58,  4.20it/s]
+  8%|▊         | 8897/112100 [34:12<7:01:50,  4.08it/s]
+  8%|▊         | 8898/112100 [34:12<6:57:56,  4.12it/s]
+  8%|▊         | 8899/112100 [34:12<7:04:40,  4.05it/s]
+  8%|▊         | 8900/112100 [34:13<6:59:00,  4.10it/s]
+                                                       
+
+  8%|▊         | 8900/112100 [34:13<6:59:00,  4.10it/s]{'loss': '1.229', 'grad_norm': '1.664', 'learning_rate': '4.603e-05', 'epoch': '7.94'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+
+  8%|▊         | 8901/112100 [34:15<24:47:52,  1.16it/s]
+  8%|▊         | 8902/112100 [34:15<19:35:15,  1.46it/s]
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+  8%|▊         | 8905/112100 [34:16<10:45:11,  2.67it/s]
+  8%|▊         | 8906/112100 [34:16<9:22:27,  3.06it/s] 
+  8%|▊         | 8907/112100 [34:16<8:22:56,  3.42it/s]
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+  8%|▊         | 8909/112100 [34:17<7:14:39,  3.96it/s]
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+  8%|▊         | 8954/112100 [34:26<5:39:43,  5.06it/s]
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+  8%|▊         | 8960/112100 [34:27<5:32:44,  5.17it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+
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+                                                       
+
+  8%|▊         | 9000/112100 [34:38<6:49:17,  4.20it/s]{'loss': '1.228', 'grad_norm': '1.362', 'learning_rate': '4.599e-05', 'epoch': '8.029'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+
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+  8%|▊         | 9067/112100 [34:55<6:24:12,  4.47it/s]
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+  8%|▊         | 9078/112100 [34:57<6:30:35,  4.40it/s]
+  8%|▊         | 9079/112100 [34:58<6:25:02,  4.46it/s]
+  8%|▊         | 9080/112100 [34:58<6:20:10,  4.52it/s]
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+  8%|▊         | 9083/112100 [34:58<6:24:39,  4.46it/s]
+  8%|▊         | 9084/112100 [34:59<6:17:10,  4.55it/s]
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+  8%|▊         | 9087/112100 [34:59<5:55:42,  4.83it/s]
+  8%|▊         | 9088/112100 [35:00<5:57:42,  4.80it/s]
+  8%|▊         | 9089/112100 [35:00<5:56:32,  4.82it/s]
+  8%|▊         | 9090/112100 [35:00<5:59:45,  4.77it/s]
+  8%|▊         | 9091/112100 [35:00<6:03:53,  4.72it/s]
+  8%|▊         | 9092/112100 [35:00<6:02:40,  4.73it/s]
+  8%|▊         | 9093/112100 [35:01<5:58:16,  4.79it/s]
+  8%|▊         | 9094/112100 [35:01<5:50:31,  4.90it/s]
+  8%|▊         | 9095/112100 [35:01<5:46:56,  4.95it/s]
+  8%|▊         | 9096/112100 [35:01<5:43:48,  4.99it/s]
+  8%|▊         | 9097/112100 [35:01<5:39:30,  5.06it/s]
+  8%|▊         | 9098/112100 [35:02<5:39:34,  5.06it/s]
+  8%|▊         | 9099/112100 [35:02<5:39:13,  5.06it/s]
+  8%|▊         | 9100/112100 [35:02<5:42:22,  5.01it/s]
+                                                       
+
+  8%|▊         | 9100/112100 [35:02<5:42:22,  5.01it/s]{'loss': '1.227', 'grad_norm': '1.394', 'learning_rate': '4.594e-05', 'epoch': '8.118'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+
+  8%|▊         | 9101/112100 [35:04<23:15:06,  1.23it/s]
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+  8%|▊         | 9107/112100 [35:05<8:10:35,  3.50it/s]
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+  8%|▊         | 9178/112100 [35:21<6:38:46,  4.30it/s]
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+  8%|▊         | 9180/112100 [35:21<6:36:13,  4.33it/s]
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+  8%|▊         | 9182/112100 [35:22<6:39:27,  4.29it/s]
+  8%|▊         | 9183/112100 [35:22<6:31:10,  4.38it/s]
+  8%|▊         | 9184/112100 [35:22<6:40:58,  4.28it/s]
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+  8%|▊         | 9189/112100 [35:24<6:51:44,  4.17it/s]
+  8%|▊         | 9190/112100 [35:24<6:58:29,  4.10it/s]
+  8%|▊         | 9191/112100 [35:24<6:55:08,  4.13it/s]
+  8%|▊         | 9192/112100 [35:24<6:56:39,  4.12it/s]
+  8%|▊         | 9193/112100 [35:24<6:53:58,  4.14it/s]
+  8%|▊         | 9194/112100 [35:25<6:58:06,  4.10it/s]
+  8%|▊         | 9195/112100 [35:25<6:56:49,  4.11it/s]
+  8%|▊         | 9196/112100 [35:25<6:54:20,  4.14it/s]
+  8%|▊         | 9197/112100 [35:25<6:55:22,  4.13it/s]
+  8%|▊         | 9198/112100 [35:26<7:02:26,  4.06it/s]
+  8%|▊         | 9199/112100 [35:26<6:58:14,  4.10it/s]
+  8%|▊         | 9200/112100 [35:26<6:53:00,  4.15it/s]
+                                                       
+
+  8%|▊         | 9200/112100 [35:26<6:53:00,  4.15it/s]{'loss': '1.227', 'grad_norm': '1.457', 'learning_rate': '4.59e-05', 'epoch': '8.207'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
+  8%|▊         | 9201/112100 [35:29<25:43:58,  1.11it/s]
+  8%|▊         | 9202/112100 [35:29<19:56:16,  1.43it/s]
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+  8%|▊         | 9214/112100 [35:32<7:05:43,  4.03it/s]
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+  8%|▊         | 9225/112100 [35:34<6:49:29,  4.19it/s]
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+  8%|▊         | 9231/112100 [35:36<6:31:05,  4.38it/s]
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+  8%|▊         | 9246/112100 [35:39<6:21:32,  4.49it/s]
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+  8%|▊         | 9248/112100 [35:40<6:03:04,  4.72it/s]
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+  8%|▊         | 9251/112100 [35:40<5:17:54,  5.39it/s]
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+  8%|▊         | 9254/112100 [35:41<5:00:23,  5.71it/s]
+  8%|▊         | 9255/112100 [35:41<4:58:04,  5.75it/s]
+  8%|▊         | 9256/112100 [35:41<4:58:58,  5.73it/s]
+  8%|▊         | 9257/112100 [35:41<5:00:56,  5.70it/s]
+  8%|▊         | 9258/112100 [35:41<5:01:01,  5.69it/s]
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+  8%|▊         | 9260/112100 [35:42<5:02:48,  5.66it/s]
+  8%|▊         | 9261/112100 [35:42<5:06:19,  5.60it/s]
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+  8%|▊         | 9264/112100 [35:42<5:08:09,  5.56it/s]
+  8%|▊         | 9265/112100 [35:43<5:08:51,  5.55it/s]
+  8%|▊         | 9266/112100 [35:43<5:11:58,  5.49it/s]
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+  8%|▊         | 9268/112100 [35:43<5:15:53,  5.43it/s]
+  8%|▊         | 9269/112100 [35:43<5:20:18,  5.35it/s]
+  8%|▊         | 9270/112100 [35:43<5:25:16,  5.27it/s]
+  8%|▊         | 9271/112100 [35:44<5:32:32,  5.15it/s]
+  8%|▊         | 9272/112100 [35:44<5:34:23,  5.13it/s]
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+  8%|▊         | 9275/112100 [35:44<5:39:30,  5.05it/s]
+  8%|▊         | 9276/112100 [35:45<5:34:04,  5.13it/s]
+  8%|▊         | 9277/112100 [35:45<5:44:29,  4.97it/s]
+  8%|▊         | 9278/112100 [35:45<5:52:30,  4.86it/s]
+  8%|▊         | 9279/112100 [35:45<5:54:27,  4.83it/s]
+  8%|▊         | 9280/112100 [35:46<5:59:07,  4.77it/s]
+  8%|▊         | 9281/112100 [35:46<5:57:53,  4.79it/s]
+  8%|▊         | 9282/112100 [35:46<5:57:52,  4.79it/s]
+  8%|▊         | 9283/112100 [35:46<6:00:44,  4.75it/s]
+  8%|▊         | 9284/112100 [35:46<5:58:33,  4.78it/s]
+  8%|▊         | 9285/112100 [35:47<6:00:17,  4.76it/s]
+  8%|▊         | 9286/112100 [35:47<5:59:14,  4.77it/s]
+  8%|▊         | 9287/112100 [35:47<6:01:18,  4.74it/s]
+  8%|▊         | 9288/112100 [35:47<6:01:23,  4.74it/s]
+  8%|▊         | 9289/112100 [35:47<6:02:40,  4.72it/s]
+  8%|▊         | 9290/112100 [35:48<6:04:53,  4.70it/s]
+  8%|▊         | 9291/112100 [35:48<6:06:05,  4.68it/s]
+  8%|▊         | 9292/112100 [35:48<6:06:35,  4.67it/s]
+  8%|▊         | 9293/112100 [35:48<6:08:04,  4.66it/s]
+  8%|▊         | 9294/112100 [35:49<6:07:49,  4.66it/s]
+  8%|▊         | 9295/112100 [35:49<6:08:49,  4.65it/s]
+  8%|▊         | 9296/112100 [35:49<6:04:36,  4.70it/s]
+  8%|▊         | 9297/112100 [35:49<6:05:28,  4.69it/s]
+  8%|▊         | 9298/112100 [35:49<6:04:37,  4.70it/s]
+  8%|▊         | 9299/112100 [35:50<6:01:26,  4.74it/s]
+  8%|▊         | 9300/112100 [35:50<6:01:19,  4.74it/s]
+                                                       
+
+  8%|▊         | 9300/112100 [35:50<6:01:19,  4.74it/s]{'loss': '1.227', 'grad_norm': '1.292', 'learning_rate': '4.585e-05', 'epoch': '8.296'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+
+  8%|▊         | 9301/112100 [35:52<25:08:37,  1.14it/s]
+  8%|▊         | 9302/112100 [35:52<19:15:03,  1.48it/s]
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+  8%|▊         | 9304/112100 [35:53<12:58:51,  2.20it/s]
+  8%|▊         | 9305/112100 [35:53<11:01:30,  2.59it/s]
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+  8%|▊         | 9307/112100 [35:54<8:41:38,  3.28it/s]
+  8%|▊         | 9308/112100 [35:54<8:13:53,  3.47it/s]
+  8%|▊         | 9309/112100 [35:54<7:48:35,  3.66it/s]
+  8%|▊         | 9310/112100 [35:54<7:29:37,  3.81it/s]
+  8%|▊         | 9311/112100 [35:55<7:07:33,  4.01it/s]
+  8%|▊         | 9312/112100 [35:55<7:03:55,  4.04it/s]
+  8%|▊         | 9313/112100 [35:55<6:52:01,  4.16it/s]
+  8%|▊         | 9314/112100 [35:55<6:47:28,  4.20it/s]
+  8%|▊         | 9315/112100 [35:55<6:39:39,  4.29it/s]
+  8%|▊         | 9316/112100 [35:56<6:35:52,  4.33it/s]
+  8%|▊         | 9317/112100 [35:56<6:37:00,  4.31it/s]
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+  8%|▊         | 9319/112100 [35:56<6:31:49,  4.37it/s]
+  8%|▊         | 9320/112100 [35:57<6:34:52,  4.34it/s]
+  8%|▊         | 9321/112100 [35:57<6:32:37,  4.36it/s]
+  8%|▊         | 9322/112100 [35:57<6:33:05,  4.36it/s]
+  8%|▊         | 9323/112100 [35:57<6:27:47,  4.42it/s]
+  8%|▊         | 9324/112100 [35:57<6:21:54,  4.49it/s]
+  8%|▊         | 9325/112100 [35:58<6:26:14,  4.43it/s]
+  8%|▊         | 9326/112100 [35:58<6:25:18,  4.45it/s]
+  8%|▊         | 9327/112100 [35:58<6:24:41,  4.45it/s]
+  8%|▊         | 9328/112100 [35:58<6:20:20,  4.50it/s]
+  8%|▊         | 9329/112100 [35:59<6:19:49,  4.51it/s]
+  8%|▊         | 9330/112100 [35:59<6:22:46,  4.47it/s]
+  8%|▊         | 9331/112100 [35:59<6:23:00,  4.47it/s]
+  8%|▊         | 9332/112100 [35:59<6:22:36,  4.48it/s]
+  8%|▊         | 9333/112100 [35:59<6:19:23,  4.51it/s]
+  8%|▊         | 9334/112100 [36:00<6:31:02,  4.38it/s]
+  8%|▊         | 9335/112100 [36:00<6:27:21,  4.42it/s]
+  8%|▊         | 9336/112100 [36:00<6:42:28,  4.26it/s]
+  8%|▊         | 9337/112100 [36:00<6:37:31,  4.31it/s]
+  8%|▊         | 9338/112100 [36:01<6:39:39,  4.29it/s]
+  8%|▊         | 9339/112100 [36:01<6:44:35,  4.23it/s]
+  8%|▊         | 9340/112100 [36:01<6:50:34,  4.17it/s]
+  8%|▊         | 9341/112100 [36:01<6:50:10,  4.18it/s]
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+  8%|▊         | 9343/112100 [36:02<6:55:09,  4.13it/s]
+  8%|▊         | 9344/112100 [36:02<6:49:07,  4.19it/s]
+  8%|▊         | 9345/112100 [36:02<6:33:48,  4.35it/s]
+  8%|▊         | 9346/112100 [36:03<6:25:17,  4.44it/s]
+  8%|▊         | 9347/112100 [36:03<6:20:38,  4.50it/s]
+  8%|▊         | 9348/112100 [36:03<6:12:30,  4.60it/s]
+  8%|▊         | 9349/112100 [36:03<6:09:23,  4.64it/s]
+  8%|▊         | 9350/112100 [36:03<5:59:46,  4.76it/s]
+  8%|▊         | 9351/112100 [36:04<6:01:00,  4.74it/s]
+  8%|▊         | 9352/112100 [36:04<6:03:28,  4.71it/s]
+  8%|▊         | 9353/112100 [36:04<6:00:17,  4.75it/s]
+  8%|▊         | 9354/112100 [36:04<6:07:09,  4.66it/s]
+  8%|▊         | 9355/112100 [36:04<6:08:19,  4.65it/s]
+  8%|▊         | 9356/112100 [36:05<6:07:40,  4.66it/s]
+  8%|▊         | 9357/112100 [36:05<6:00:36,  4.75it/s]
+  8%|▊         | 9358/112100 [36:05<6:01:16,  4.74it/s]
+  8%|▊         | 9359/112100 [36:05<5:51:09,  4.88it/s]
+  8%|▊         | 9360/112100 [36:05<5:54:12,  4.83it/s]
+  8%|▊         | 9361/112100 [36:06<5:50:57,  4.88it/s]
+  8%|▊         | 9362/112100 [36:06<5:39:04,  5.05it/s]
+  8%|▊         | 9363/112100 [36:06<5:47:32,  4.93it/s]
+  8%|▊         | 9364/112100 [36:06<5:45:15,  4.96it/s]
+  8%|▊         | 9365/112100 [36:06<5:48:58,  4.91it/s]
+  8%|▊         | 9366/112100 [36:07<5:57:27,  4.79it/s]
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+  8%|▊         | 9369/112100 [36:07<6:24:18,  4.46it/s]
+  8%|▊         | 9370/112100 [36:08<6:16:49,  4.54it/s]
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+  8%|▊         | 9373/112100 [36:08<6:30:01,  4.39it/s]
+  8%|▊         | 9374/112100 [36:09<6:36:05,  4.32it/s]
+  8%|▊         | 9375/112100 [36:09<6:34:37,  4.34it/s]
+  8%|▊         | 9376/112100 [36:09<6:42:15,  4.26it/s]
+  8%|▊         | 9377/112100 [36:09<6:45:19,  4.22it/s]
+  8%|▊         | 9378/112100 [36:09<6:45:52,  4.22it/s]
+  8%|▊         | 9379/112100 [36:10<6:44:42,  4.23it/s]
+  8%|▊         | 9380/112100 [36:10<6:46:19,  4.21it/s]
+  8%|▊         | 9381/112100 [36:10<6:42:17,  4.26it/s]
+  8%|▊         | 9382/112100 [36:10<6:43:15,  4.25it/s]
+  8%|▊         | 9383/112100 [36:11<6:39:20,  4.29it/s]
+  8%|▊         | 9384/112100 [36:11<6:44:03,  4.24it/s]
+  8%|▊         | 9385/112100 [36:11<6:41:52,  4.26it/s]
+  8%|▊         | 9386/112100 [36:11<6:42:37,  4.25it/s]
+  8%|▊         | 9387/112100 [36:12<6:48:31,  4.19it/s]
+  8%|▊         | 9388/112100 [36:12<6:55:24,  4.12it/s]
+  8%|▊         | 9389/112100 [36:12<6:56:30,  4.11it/s]
+  8%|▊         | 9390/112100 [36:12<6:56:30,  4.11it/s]
+  8%|▊         | 9391/112100 [36:13<6:54:54,  4.13it/s]
+  8%|▊         | 9392/112100 [36:13<6:57:45,  4.10it/s]
+  8%|▊         | 9393/112100 [36:13<6:57:54,  4.10it/s]
+  8%|▊         | 9394/112100 [36:13<6:56:32,  4.11it/s]
+  8%|▊         | 9395/112100 [36:14<6:56:02,  4.11it/s]
+  8%|▊         | 9396/112100 [36:14<6:55:13,  4.12it/s]
+  8%|▊         | 9397/112100 [36:14<6:55:39,  4.12it/s]
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+  8%|▊         | 9399/112100 [36:15<6:56:55,  4.11it/s]
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+                                                       
+
+  8%|▊         | 9400/112100 [36:15<6:57:53,  4.10it/s]{'loss': '1.226', 'grad_norm': '1.306', 'learning_rate': '4.581e-05', 'epoch': '8.386'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                       
+
+  8%|▊         | 9500/112100 [36:38<6:54:47,  4.12it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.227', 'grad_norm': '1.57', 'learning_rate': '4.576e-05', 'epoch': '8.475'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.39it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.38it/s]
+
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+  9%|▊         | 9596/112100 [37:02<6:57:36,  4.09it/s]
+  9%|▊         | 9597/112100 [37:02<7:01:12,  4.06it/s]
+  9%|▊         | 9598/112100 [37:02<6:58:55,  4.08it/s]
+  9%|▊         | 9599/112100 [37:02<6:56:12,  4.10it/s]
+  9%|▊         | 9600/112100 [37:03<7:00:42,  4.06it/s]
+                                                       
+
+  9%|▊         | 9600/112100 [37:03<7:00:42,  4.06it/s]{'loss': '1.226', 'grad_norm': '1.341', 'learning_rate': '4.572e-05', 'epoch': '8.564'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+
+  9%|▊         | 9601/112100 [37:05<24:11:38,  1.18it/s]
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+  9%|▊         | 9607/112100 [37:06<8:12:24,  3.47it/s]
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+                                                       
+
+  9%|▊         | 9700/112100 [37:25<6:55:36,  4.11it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.226', 'grad_norm': '1.401', 'learning_rate': '4.567e-05', 'epoch': '8.653'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+
+  9%|▊         | 9701/112100 [37:27<22:28:58,  1.27it/s]
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+  9%|▊         | 9781/112100 [37:46<6:10:41,  4.60it/s]
+  9%|▊         | 9782/112100 [37:46<6:11:56,  4.58it/s]
+  9%|▊         | 9783/112100 [37:46<6:06:40,  4.65it/s]
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+  9%|▊         | 9800/112100 [37:50<5:52:36,  4.84it/s]
+                                                       
+
+  9%|▊         | 9800/112100 [37:50<5:52:36,  4.84it/s]{'loss': '1.227', 'grad_norm': '1.32', 'learning_rate': '4.563e-05', 'epoch': '8.743'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+
+  9%|▊         | 9801/112100 [37:52<21:58:53,  1.29it/s]
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+  9%|▊         | 9806/112100 [37:53<8:17:05,  3.43it/s]
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+                                                       
+
+  9%|▉         | 9900/112100 [38:13<6:36:42,  4.29it/s]{'loss': '1.226', 'grad_norm': '1.374', 'learning_rate': '4.559e-05', 'epoch': '8.832'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                        
+
+  9%|▉         | 10000/112100 [38:37<4:51:13,  5.84it/s]{'loss': '1.226', 'grad_norm': '1.36', 'learning_rate': '4.554e-05', 'epoch': '8.921'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+  9%|▉         | 10001/112100 [38:39<24:18:27,  1.17it/s]
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+                                                        
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+  9%|▉         | 10100/112100 [39:03<6:31:01,  4.35it/s]{'loss': '1.225', 'grad_norm': '1.145', 'learning_rate': '4.55e-05', 'epoch': '9.01'}
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+                                                        
+
+  9%|▉         | 10200/112100 [39:27<6:28:30,  4.37it/s]{'loss': '1.224', 'grad_norm': '1.329', 'learning_rate': '4.545e-05', 'epoch': '9.099'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                        
+
+  9%|▉         | 10300/112100 [39:52<6:22:52,  4.43it/s]{'loss': '1.224', 'grad_norm': '1.678', 'learning_rate': '4.541e-05', 'epoch': '9.188'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                        
+
+  9%|▉         | 10400/112100 [40:14<6:55:52,  4.08it/s]{'loss': '1.225', 'grad_norm': '1.411', 'learning_rate': '4.536e-05', 'epoch': '9.278'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                        
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.224', 'grad_norm': '1.189', 'learning_rate': '4.532e-05', 'epoch': '9.367'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                        
+
+  9%|▉         | 10600/112100 [41:03<6:54:15,  4.08it/s]{'loss': '1.223', 'grad_norm': '1.45', 'learning_rate': '4.527e-05', 'epoch': '9.456'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                        
+
+ 10%|▉         | 10700/112100 [41:27<5:35:37,  5.04it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.224', 'grad_norm': '1.413', 'learning_rate': '4.523e-05', 'epoch': '9.545'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+
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+                                                        
+
+ 10%|▉         | 10800/112100 [41:51<6:24:25,  4.39it/s]{'loss': '1.223', 'grad_norm': '1.424', 'learning_rate': '4.518e-05', 'epoch': '9.635'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.43it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.43it/s]
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+                                                        
+
+ 10%|▉         | 10900/112100 [42:14<5:48:59,  4.83it/s]{'loss': '1.226', 'grad_norm': '1.105', 'learning_rate': '4.514e-05', 'epoch': '9.724'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                        
+
+ 10%|▉         | 11000/112100 [42:39<6:38:37,  4.23it/s]{'loss': '1.223', 'grad_norm': '1.144', 'learning_rate': '4.51e-05', 'epoch': '9.813'}
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                        
+
+ 10%|▉         | 11100/112100 [43:02<6:24:18,  4.38it/s]{'loss': '1.226', 'grad_norm': '1.323', 'learning_rate': '4.505e-05', 'epoch': '9.902'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                        
+
+ 10%|▉         | 11200/112100 [43:27<6:37:50,  4.23it/s]{'loss': '1.224', 'grad_norm': '1.39', 'learning_rate': '4.501e-05', 'epoch': '9.992'}
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+                                                        
+
+ 10%|█         | 11300/112100 [43:53<6:36:38,  4.24it/s]{'loss': '1.223', 'grad_norm': '1.743', 'learning_rate': '4.496e-05', 'epoch': '10.08'}
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+                                                        
+
+ 10%|█         | 11400/112100 [44:17<5:00:16,  5.59it/s]{'loss': '1.221', 'grad_norm': '1.163', 'learning_rate': '4.492e-05', 'epoch': '10.17'}
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+                                                        
+
+ 10%|█         | 11500/112100 [44:41<6:06:21,  4.58it/s]{'loss': '1.223', 'grad_norm': '1.273', 'learning_rate': '4.487e-05', 'epoch': '10.26'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                        
+
+ 10%|█         | 11600/112100 [45:04<5:02:22,  5.54it/s]{'loss': '1.223', 'grad_norm': '1.503', 'learning_rate': '4.483e-05', 'epoch': '10.35'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                        
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.224', 'grad_norm': '1.517', 'learning_rate': '4.478e-05', 'epoch': '10.44'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
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+                                                        
+
+ 11%|█         | 11800/112100 [45:53<6:46:08,  4.12it/s]{'loss': '1.222', 'grad_norm': '1.339', 'learning_rate': '4.474e-05', 'epoch': '10.53'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.39it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.39it/s]
+
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+                                                        
+
+ 11%|█         | 11900/112100 [46:18<6:39:15,  4.18it/s]{'loss': '1.221', 'grad_norm': '1.144', 'learning_rate': '4.469e-05', 'epoch': '10.62'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.42it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.42it/s]
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+                                                        
+
+ 11%|█         | 12000/112100 [46:40<5:43:07,  4.86it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.221', 'grad_norm': '1.198', 'learning_rate': '4.465e-05', 'epoch': '10.71'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.41it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.41it/s]
+
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+                                                        
+
+ 11%|█         | 12100/112100 [47:04<6:05:58,  4.55it/s]{'loss': '1.222', 'grad_norm': '1.618', 'learning_rate': '4.46e-05', 'epoch': '10.79'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                        
+
+ 11%|█         | 12200/112100 [47:27<5:09:13,  5.38it/s]{'loss': '1.221', 'grad_norm': '1.22', 'learning_rate': '4.456e-05', 'epoch': '10.88'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                        
+
+ 11%|█         | 12300/112100 [47:53<6:08:48,  4.51it/s]{'loss': '1.223', 'grad_norm': '1.365', 'learning_rate': '4.452e-05', 'epoch': '10.97'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                        
+
+ 11%|█         | 12400/112100 [48:18<6:41:15,  4.14it/s]{'loss': '1.221', 'grad_norm': '1.396', 'learning_rate': '4.447e-05', 'epoch': '11.06'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                        
+
+ 11%|█         | 12500/112100 [48:43<5:35:57,  4.94it/s]{'loss': '1.221', 'grad_norm': '1.408', 'learning_rate': '4.443e-05', 'epoch': '11.15'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                        
+
+ 11%|█         | 12600/112100 [49:06<6:32:43,  4.22it/s]{'loss': '1.223', 'grad_norm': '1.297', 'learning_rate': '4.438e-05', 'epoch': '11.24'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
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+                                                        
+
+ 11%|█▏        | 12700/112100 [49:30<5:15:22,  5.25it/s]{'loss': '1.22', 'grad_norm': '1.35', 'learning_rate': '4.434e-05', 'epoch': '11.33'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+
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+                                                        
+
+ 11%|█▏        | 12800/112100 [49:54<6:37:42,  4.16it/s]{'loss': '1.22', 'grad_norm': '1.158', 'learning_rate': '4.429e-05', 'epoch': '11.42'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
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+ 12%|█▏        | 12900/112100 [50:17<5:23:28,  5.11it/s]
+                                                        
+
+ 12%|█▏        | 12900/112100 [50:17<5:23:28,  5.11it/s]{'loss': '1.221', 'grad_norm': '1.186', 'learning_rate': '4.425e-05', 'epoch': '11.51'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                        
+
+ 12%|█▏        | 13000/112100 [50:43<6:22:03,  4.32it/s]{'loss': '1.221', 'grad_norm': '1.421', 'learning_rate': '4.42e-05', 'epoch': '11.6'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
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+ 12%|█▏        | 13100/112100 [51:06<6:14:30,  4.41it/s]
+                                                        
+
+ 12%|█▏        | 13100/112100 [51:06<6:14:30,  4.41it/s]{'loss': '1.22', 'grad_norm': '1.218', 'learning_rate': '4.416e-05', 'epoch': '11.69'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
+
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+ 12%|█▏        | 13200/112100 [51:31<5:57:39,  4.61it/s]
+                                                        
+
+ 12%|█▏        | 13200/112100 [51:31<5:57:39,  4.61it/s]{'loss': '1.221', 'grad_norm': '1.266', 'learning_rate': '4.411e-05', 'epoch': '11.78'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+
+ 12%|█▏        | 13201/112100 [51:34<24:15:59,  1.13it/s]
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+                                                        
+
+ 12%|█▏        | 13300/112100 [51:55<6:25:47,  4.27it/s]{'loss': '1.22', 'grad_norm': '1.254', 'learning_rate': '4.407e-05', 'epoch': '11.86'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+ 12%|█▏        | 13400/112100 [52:20<4:55:07,  5.57it/s]
+                                                        
+
+ 12%|█▏        | 13400/112100 [52:20<4:55:07,  5.57it/s]{'loss': '1.222', 'grad_norm': '1.515', 'learning_rate': '4.403e-05', 'epoch': '11.95'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+
+ 12%|█▏        | 13401/112100 [52:22<23:12:21,  1.18it/s]
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+                                                        
+
+ 12%|█▏        | 13500/112100 [52:46<6:10:47,  4.43it/s]{'loss': '1.221', 'grad_norm': '1.317', 'learning_rate': '4.398e-05', 'epoch': '12.04'}
+
+
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+                                                        
+
+ 12%|█▏        | 13600/112100 [53:09<5:27:18,  5.02it/s]{'loss': '1.22', 'grad_norm': '1.377', 'learning_rate': '4.394e-05', 'epoch': '12.13'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
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+                                                        
+
+ 12%|█▏        | 13700/112100 [53:34<6:15:14,  4.37it/s]{'loss': '1.218', 'grad_norm': '1.396', 'learning_rate': '4.389e-05', 'epoch': '12.22'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.63it/s]
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+                                                        
+
+ 12%|█▏        | 13800/112100 [53:57<6:19:03,  4.32it/s]{'loss': '1.221', 'grad_norm': '1.423', 'learning_rate': '4.385e-05', 'epoch': '12.31'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                        
+
+ 12%|█▏        | 13900/112100 [54:22<6:06:23,  4.47it/s]{'loss': '1.221', 'grad_norm': '1.422', 'learning_rate': '4.38e-05', 'epoch': '12.4'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+ 12%|█▏        | 14000/112100 [54:46<6:10:08,  4.42it/s]
+                                                        
+
+ 12%|█▏        | 14000/112100 [54:46<6:10:08,  4.42it/s]{'loss': '1.219', 'grad_norm': '1.287', 'learning_rate': '4.376e-05', 'epoch': '12.49'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                        
+
+ 13%|█▎        | 14100/112100 [55:10<5:26:05,  5.01it/s]{'loss': '1.219', 'grad_norm': '1.331', 'learning_rate': '4.371e-05', 'epoch': '12.58'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                        
+
+ 13%|█▎        | 14200/112100 [55:34<6:11:34,  4.39it/s]{'loss': '1.219', 'grad_norm': '1.143', 'learning_rate': '4.367e-05', 'epoch': '12.67'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                        
+
+ 13%|█▎        | 14300/112100 [55:58<4:55:23,  5.52it/s]{'loss': '1.219', 'grad_norm': '1.234', 'learning_rate': '4.362e-05', 'epoch': '12.76'}
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+                                                        
+
+ 13%|█▎        | 14400/112100 [56:23<5:59:35,  4.53it/s]{'loss': '1.221', 'grad_norm': '0.9764', 'learning_rate': '4.358e-05', 'epoch': '12.85'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                        
+
+ 13%|█▎        | 14500/112100 [56:46<6:32:03,  4.15it/s]{'loss': '1.221', 'grad_norm': '1.313', 'learning_rate': '4.353e-05', 'epoch': '12.94'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                        
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.218', 'grad_norm': '2.011', 'learning_rate': '4.349e-05', 'epoch': '13.02'}
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+                                                        
+
+ 13%|█▎        | 14700/112100 [57:36<6:33:21,  4.13it/s]{'loss': '1.217', 'grad_norm': '1.064', 'learning_rate': '4.345e-05', 'epoch': '13.11'}
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.36it/s]
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+                                                        
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.218', 'grad_norm': '1.128', 'learning_rate': '4.34e-05', 'epoch': '13.2'}
+
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+                                                        
+
+ 13%|█▎        | 14900/112100 [58:24<6:28:58,  4.16it/s]{'loss': '1.22', 'grad_norm': '1.658', 'learning_rate': '4.336e-05', 'epoch': '13.29'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                        
+
+ 13%|█▎        | 15000/112100 [58:47<5:19:06,  5.07it/s]{'loss': '1.218', 'grad_norm': '1.102', 'learning_rate': '4.331e-05', 'epoch': '13.38'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                        
+
+ 13%|█▎        | 15100/112100 [59:13<6:28:28,  4.16it/s]{'loss': '1.22', 'grad_norm': '1.267', 'learning_rate': '4.327e-05', 'epoch': '13.47'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                        
+
+ 14%|█▎        | 15200/112100 [59:36<6:00:47,  4.48it/s]{'loss': '1.219', 'grad_norm': '1.464', 'learning_rate': '4.322e-05', 'epoch': '13.56'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 14%|█▎        | 15300/112100 [1:00:01<5:50:42,  4.60it/s]{'loss': '1.218', 'grad_norm': '1.713', 'learning_rate': '4.318e-05', 'epoch': '13.65'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 14%|█▎        | 15400/112100 [1:00:24<5:52:12,  4.58it/s]{'loss': '1.219', 'grad_norm': '1.59', 'learning_rate': '4.313e-05', 'epoch': '13.74'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 14%|█▍        | 15500/112100 [1:00:49<5:15:05,  5.11it/s]{'loss': '1.22', 'grad_norm': '1.478', 'learning_rate': '4.309e-05', 'epoch': '13.83'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                          
+
+ 14%|█▍        | 15600/112100 [1:01:13<6:12:52,  4.31it/s]{'loss': '1.219', 'grad_norm': '1.157', 'learning_rate': '4.304e-05', 'epoch': '13.92'}
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
+ 14%|█▍        | 15700/112100 [1:01:38<7:54:03,  3.39it/s]{'loss': '1.218', 'grad_norm': '1.192', 'learning_rate': '4.3e-05', 'epoch': '14.01'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                          
+
+ 14%|█▍        | 15800/112100 [1:02:03<6:26:56,  4.15it/s]{'loss': '1.218', 'grad_norm': '1.241', 'learning_rate': '4.296e-05', 'epoch': '14.09'}
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+                                                          
+
+ 14%|█▍        | 15900/112100 [1:02:26<6:28:12,  4.13it/s]{'loss': '1.217', 'grad_norm': '1.322', 'learning_rate': '4.291e-05', 'epoch': '14.18'}
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+                                                          
+
+ 14%|█▍        | 16000/112100 [1:02:51<6:28:21,  4.12it/s]{'loss': '1.216', 'grad_norm': '1.515', 'learning_rate': '4.287e-05', 'epoch': '14.27'}
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+                                                          
+
+ 14%|█▍        | 16100/112100 [1:03:14<6:26:50,  4.14it/s]{'loss': '1.219', 'grad_norm': '1.42', 'learning_rate': '4.282e-05', 'epoch': '14.36'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 14%|█▍        | 16200/112100 [1:03:39<5:38:51,  4.72it/s]{'loss': '1.219', 'grad_norm': '1.494', 'learning_rate': '4.278e-05', 'epoch': '14.45'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.218', 'grad_norm': '1.322', 'learning_rate': '4.273e-05', 'epoch': '14.54'}
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
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+ 15%|█▍        | 16400/112100 [1:04:27<4:58:37,  5.34it/s]{'loss': '1.217', 'grad_norm': '1.346', 'learning_rate': '4.269e-05', 'epoch': '14.63'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 15%|█▍        | 16500/112100 [1:04:51<6:03:18,  4.39it/s]{'loss': '1.218', 'grad_norm': '1.407', 'learning_rate': '4.264e-05', 'epoch': '14.72'}
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+                                                          
+
+ 15%|█▍        | 16600/112100 [1:05:13<5:30:27,  4.82it/s]{'loss': '1.217', 'grad_norm': '1.16', 'learning_rate': '4.26e-05', 'epoch': '14.81'}
+
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+                                                          
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.218', 'grad_norm': '1.354', 'learning_rate': '4.251e-05', 'epoch': '14.99'}
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 15%|█▌        | 16900/112100 [1:06:27<5:11:43,  5.09it/s]{'loss': '1.216', 'grad_norm': '1.284', 'learning_rate': '4.246e-05', 'epoch': '15.08'}
+
+
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+                                                          
+
+ 15%|█▌        | 17000/112100 [1:06:50<5:56:34,  4.45it/s]{'loss': '1.216', 'grad_norm': '1.226', 'learning_rate': '4.242e-05', 'epoch': '15.17'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                          
+
+ 15%|█▌        | 17100/112100 [1:07:15<5:04:29,  5.20it/s]{'loss': '1.217', 'grad_norm': '1.642', 'learning_rate': '4.238e-05', 'epoch': '15.25'}
+
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+                                                          
+
+ 15%|█▌        | 17200/112100 [1:07:39<6:11:18,  4.26it/s]{'loss': '1.216', 'grad_norm': '1.286', 'learning_rate': '4.233e-05', 'epoch': '15.34'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 15%|█▌        | 17300/112100 [1:08:03<5:24:50,  4.86it/s]{'loss': '1.216', 'grad_norm': '1.228', 'learning_rate': '4.229e-05', 'epoch': '15.43'}
+
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+                                                          
+
+ 16%|█▌        | 17400/112100 [1:08:28<6:05:56,  4.31it/s]{'loss': '1.217', 'grad_norm': '1.025', 'learning_rate': '4.224e-05', 'epoch': '15.52'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
+ 16%|█▌        | 17500/112100 [1:08:51<5:27:01,  4.82it/s]{'loss': '1.217', 'grad_norm': '1.77', 'learning_rate': '4.22e-05', 'epoch': '15.61'}
+
+
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+                                                          
+
+ 16%|█▌        | 17600/112100 [1:09:16<5:45:10,  4.56it/s]{'loss': '1.218', 'grad_norm': '1.283', 'learning_rate': '4.215e-05', 'epoch': '15.7'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 16%|█▌        | 17700/112100 [1:09:39<6:06:39,  4.29it/s]{'loss': '1.219', 'grad_norm': '1.356', 'learning_rate': '4.211e-05', 'epoch': '15.79'}
+
+
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+                                                          
+
+ 16%|█▌        | 17800/112100 [1:10:02<6:12:50,  4.22it/s]{'loss': '1.216', 'grad_norm': '1.571', 'learning_rate': '4.206e-05', 'epoch': '15.88'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 16%|█▌        | 17900/112100 [1:10:24<4:57:03,  5.29it/s]{'loss': '1.215', 'grad_norm': '1.336', 'learning_rate': '4.202e-05', 'epoch': '15.97'}
+
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+                                                          
+
+ 16%|█▌        | 18000/112100 [1:10:52<6:06:41,  4.28it/s]{'loss': '1.215', 'grad_norm': '1.568', 'learning_rate': '4.197e-05', 'epoch': '16.06'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.40it/s]
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+                                                          
+
+ 16%|█▌        | 18100/112100 [1:11:14<5:59:20,  4.36it/s]{'loss': '1.215', 'grad_norm': '0.9653', 'learning_rate': '4.193e-05', 'epoch': '16.15'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
+ 16%|█▌        | 18200/112100 [1:11:40<5:30:11,  4.74it/s]{'loss': '1.217', 'grad_norm': '1.227', 'learning_rate': '4.189e-05', 'epoch': '16.24'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 16%|█▋        | 18300/112100 [1:12:04<6:13:03,  4.19it/s]{'loss': '1.216', 'grad_norm': '1.134', 'learning_rate': '4.184e-05', 'epoch': '16.32'}
+
+
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+                                                          
+
+ 16%|█▋        | 18400/112100 [1:12:28<4:54:30,  5.30it/s]{'loss': '1.215', 'grad_norm': '1.49', 'learning_rate': '4.18e-05', 'epoch': '16.41'}
+
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.215', 'grad_norm': '1.564', 'learning_rate': '4.175e-05', 'epoch': '16.5'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                          
+
+ 17%|█▋        | 18600/112100 [1:13:13<4:13:48,  6.14it/s]{'loss': '1.217', 'grad_norm': '1.215', 'learning_rate': '4.171e-05', 'epoch': '16.59'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                          
+
+ 17%|█▋        | 18700/112100 [1:13:38<5:27:35,  4.75it/s]{'loss': '1.217', 'grad_norm': '1.06', 'learning_rate': '4.166e-05', 'epoch': '16.68'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+
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+                                                          
+
+ 17%|█▋        | 18800/112100 [1:14:00<5:36:33,  4.62it/s]{'loss': '1.215', 'grad_norm': '1.541', 'learning_rate': '4.162e-05', 'epoch': '16.77'}
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.214', 'grad_norm': '1.171', 'learning_rate': '4.157e-05', 'epoch': '16.86'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
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+                                                          
+
+ 17%|█▋        | 19000/112100 [1:14:46<5:44:24,  4.51it/s]{'loss': '1.216', 'grad_norm': '1.405', 'learning_rate': '4.153e-05', 'epoch': '16.95'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
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+                                                          
+
+ 17%|█▋        | 19100/112100 [1:15:10<4:14:34,  6.09it/s]{'loss': '1.214', 'grad_norm': '1.415', 'learning_rate': '4.148e-05', 'epoch': '17.04'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 17%|█▋        | 19200/112100 [1:15:34<5:17:11,  4.88it/s]{'loss': '1.215', 'grad_norm': '1.361', 'learning_rate': '4.144e-05', 'epoch': '17.13'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 17%|█▋        | 19300/112100 [1:15:56<4:46:32,  5.40it/s]{'loss': '1.214', 'grad_norm': '1.26', 'learning_rate': '4.139e-05', 'epoch': '17.22'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 17%|█▋        | 19400/112100 [1:16:20<5:29:56,  4.68it/s]{'loss': '1.215', 'grad_norm': '1.119', 'learning_rate': '4.135e-05', 'epoch': '17.31'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 17%|█▋        | 19500/112100 [1:16:42<5:06:42,  5.03it/s]{'loss': '1.213', 'grad_norm': '1.021', 'learning_rate': '4.131e-05', 'epoch': '17.4'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 17%|█▋        | 19600/112100 [1:17:05<4:47:29,  5.36it/s]{'loss': '1.215', 'grad_norm': '1.365', 'learning_rate': '4.126e-05', 'epoch': '17.48'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 18%|█▊        | 19700/112100 [1:17:28<5:45:48,  4.45it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.215', 'grad_norm': '1.421', 'learning_rate': '4.122e-05', 'epoch': '17.57'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+
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+                                                          
+
+ 18%|█▊        | 19800/112100 [1:17:50<4:31:32,  5.67it/s]{'loss': '1.217', 'grad_norm': '1.158', 'learning_rate': '4.117e-05', 'epoch': '17.66'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.69it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
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+ 18%|█▊        | 19900/112100 [1:18:14<5:30:22,  4.65it/s]
+                                                          
+
+ 18%|█▊        | 19900/112100 [1:18:14<5:30:22,  4.65it/s]{'loss': '1.215', 'grad_norm': '1.439', 'learning_rate': '4.113e-05', 'epoch': '17.75'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+
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+                                                          
+
+ 18%|█▊        | 20000/112100 [1:18:35<5:14:03,  4.89it/s]{'loss': '1.214', 'grad_norm': '1.522', 'learning_rate': '4.108e-05', 'epoch': '17.84'}
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+                                                          
+
+ 18%|█▊        | 20100/112100 [1:18:59<5:20:59,  4.78it/s]{'loss': '1.215', 'grad_norm': '1.299', 'learning_rate': '4.104e-05', 'epoch': '17.93'}
+
+
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+                                                          
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.214', 'grad_norm': '1.133', 'learning_rate': '4.095e-05', 'epoch': '18.11'}
+
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+                                                          
+
+ 18%|█▊        | 20400/112100 [1:20:09<4:57:37,  5.13it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.214', 'grad_norm': '1.066', 'learning_rate': '4.09e-05', 'epoch': '18.2'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 18%|█▊        | 20500/112100 [1:20:31<4:12:21,  6.05it/s]{'loss': '1.215', 'grad_norm': '1.459', 'learning_rate': '4.086e-05', 'epoch': '18.29'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 18%|█▊        | 20600/112100 [1:20:56<5:01:58,  5.05it/s]{'loss': '1.215', 'grad_norm': '1.098', 'learning_rate': '4.082e-05', 'epoch': '18.38'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                          
+
+ 18%|█▊        | 20700/112100 [1:21:17<5:27:27,  4.65it/s]{'loss': '1.216', 'grad_norm': '1.642', 'learning_rate': '4.077e-05', 'epoch': '18.47'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
+
+ 19%|█▊        | 20800/112100 [1:21:41<5:03:32,  5.01it/s]{'loss': '1.215', 'grad_norm': '1.506', 'learning_rate': '4.073e-05', 'epoch': '18.56'}
+
+
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+                                                          
+
+ 19%|█▊        | 20900/112100 [1:22:03<5:42:41,  4.44it/s]{'loss': '1.212', 'grad_norm': '1.466', 'learning_rate': '4.068e-05', 'epoch': '18.64'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                          
+
+ 19%|█▊        | 21000/112100 [1:22:26<4:28:07,  5.66it/s]{'loss': '1.214', 'grad_norm': '1.443', 'learning_rate': '4.064e-05', 'epoch': '18.73'}
+
+
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+                                                          
+
+ 19%|█▉        | 21100/112100 [1:22:49<5:47:41,  4.36it/s]{'loss': '1.215', 'grad_norm': '1.28', 'learning_rate': '4.059e-05', 'epoch': '18.82'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.42it/s]
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+                                                          
+
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+
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+                                                           
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.213', 'grad_norm': '1.309', 'learning_rate': '4.05e-05', 'epoch': '19'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.214', 'grad_norm': '1.433', 'learning_rate': '4.046e-05', 'epoch': '19.09'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                          
+
+ 19%|█▉        | 21500/112100 [1:24:23<4:49:48,  5.21it/s]{'loss': '1.213', 'grad_norm': '1.491', 'learning_rate': '4.041e-05', 'epoch': '19.18'}
+
+
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+                                                          
+
+ 19%|█▉        | 21600/112100 [1:24:45<5:26:27,  4.62it/s]{'loss': '1.214', 'grad_norm': '1.348', 'learning_rate': '4.037e-05', 'epoch': '19.27'}
+
+
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+                                                          
+
+ 19%|█▉        | 21700/112100 [1:25:07<4:27:22,  5.64it/s]{'loss': '1.214', 'grad_norm': '1.146', 'learning_rate': '4.032e-05', 'epoch': '19.36'}
+
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+                                                          
+
+ 19%|█▉        | 21800/112100 [1:25:30<5:21:25,  4.68it/s]{'loss': '1.211', 'grad_norm': '1.371', 'learning_rate': '4.028e-05', 'epoch': '19.45'}
+
+
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+                                                          
+
+ 20%|█▉        | 21900/112100 [1:25:52<4:24:29,  5.68it/s]{'loss': '1.216', 'grad_norm': '1.251', 'learning_rate': '4.024e-05', 'epoch': '19.54'}
+
+
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+                                                          
+
+ 20%|█▉        | 22000/112100 [1:26:16<5:45:45,  4.34it/s]{'loss': '1.214', 'grad_norm': '1.306', 'learning_rate': '4.019e-05', 'epoch': '19.63'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.66it/s]
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+                                                          
+
+ 20%|█▉        | 22100/112100 [1:26:37<5:26:18,  4.60it/s]{'loss': '1.213', 'grad_norm': '1.339', 'learning_rate': '4.015e-05', 'epoch': '19.71'}
+
+
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+                                                          
+
+ 20%|█▉        | 22200/112100 [1:27:01<4:57:57,  5.03it/s]{'loss': '1.214', 'grad_norm': '1.447', 'learning_rate': '4.01e-05', 'epoch': '19.8'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
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+                                                          
+
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+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.215', 'grad_norm': '1.278', 'learning_rate': '4.001e-05', 'epoch': '19.98'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                          
+
+ 20%|██        | 22500/112100 [1:28:10<5:41:14,  4.38it/s]{'loss': '1.213', 'grad_norm': '1.115', 'learning_rate': '3.997e-05', 'epoch': '20.07'}
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+                                                          
+
+ 20%|██        | 22600/112100 [1:28:31<4:47:30,  5.19it/s]{'loss': '1.214', 'grad_norm': '1.252', 'learning_rate': '3.992e-05', 'epoch': '20.16'}
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+                                                          
+
+ 20%|██        | 22700/112100 [1:28:55<5:33:02,  4.47it/s]{'loss': '1.213', 'grad_norm': '1.332', 'learning_rate': '3.988e-05', 'epoch': '20.25'}
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+                                                          
+
+ 20%|██        | 22800/112100 [1:29:16<5:27:07,  4.55it/s]{'loss': '1.213', 'grad_norm': '1.263', 'learning_rate': '3.983e-05', 'epoch': '20.34'}
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.213', 'grad_norm': '1.348', 'learning_rate': '3.975e-05', 'epoch': '20.52'}
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+                                                          
+
+ 21%|██        | 23100/112100 [1:30:24<4:19:12,  5.72it/s]{'loss': '1.214', 'grad_norm': '1.315', 'learning_rate': '3.97e-05', 'epoch': '20.61'}
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+                                                          
+
+ 21%|██        | 23200/112100 [1:30:48<5:09:39,  4.78it/s]{'loss': '1.213', 'grad_norm': '2.344', 'learning_rate': '3.966e-05', 'epoch': '20.7'}
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+                                                          
+
+ 21%|██        | 23300/112100 [1:31:09<4:32:50,  5.42it/s]{'loss': '1.213', 'grad_norm': '1.164', 'learning_rate': '3.961e-05', 'epoch': '20.79'}
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+                                                          
+
+ 21%|██        | 23400/112100 [1:31:33<5:07:58,  4.80it/s]{'loss': '1.214', 'grad_norm': '1.936', 'learning_rate': '3.957e-05', 'epoch': '20.87'}
+
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+                                                          
+
+ 21%|██        | 23500/112100 [1:31:54<4:15:56,  5.77it/s]{'loss': '1.213', 'grad_norm': '1.108', 'learning_rate': '3.952e-05', 'epoch': '20.96'}
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+                                                          
+
+ 21%|██        | 23600/112100 [1:32:19<5:34:40,  4.41it/s]{'loss': '1.213', 'grad_norm': '1.34', 'learning_rate': '3.948e-05', 'epoch': '21.05'}
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+                                                          
+
+ 21%|██        | 23700/112100 [1:32:41<4:33:03,  5.40it/s]{'loss': '1.212', 'grad_norm': '1.66', 'learning_rate': '3.943e-05', 'epoch': '21.14'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.212', 'grad_norm': '1.117', 'learning_rate': '3.939e-05', 'epoch': '21.23'}
+
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+                                                          
+
+ 21%|██▏       | 23900/112100 [1:33:26<5:22:07,  4.56it/s]{'loss': '1.21', 'grad_norm': '1.359', 'learning_rate': '3.934e-05', 'epoch': '21.32'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 21%|██▏       | 24000/112100 [1:33:50<5:32:37,  4.41it/s]{'loss': '1.213', 'grad_norm': '1.231', 'learning_rate': '3.93e-05', 'epoch': '21.41'}
+
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+                                                          
+
+ 21%|██▏       | 24100/112100 [1:34:12<5:30:02,  4.44it/s]{'loss': '1.213', 'grad_norm': '1.174', 'learning_rate': '3.926e-05', 'epoch': '21.5'}
+
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+                                                          
+
+ 22%|██▏       | 24200/112100 [1:34:35<4:40:54,  5.22it/s]{'loss': '1.211', 'grad_norm': '1.043', 'learning_rate': '3.921e-05', 'epoch': '21.59'}
+
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+                                                          
+
+ 22%|██▏       | 24300/112100 [1:34:57<5:32:31,  4.40it/s]{'loss': '1.211', 'grad_norm': '1.202', 'learning_rate': '3.917e-05', 'epoch': '21.68'}
+
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+                                                          
+
+ 22%|██▏       | 24400/112100 [1:35:19<4:07:21,  5.91it/s]{'loss': '1.213', 'grad_norm': '1.279', 'learning_rate': '3.912e-05', 'epoch': '21.77'}
+
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+                                                          
+
+ 22%|██▏       | 24500/112100 [1:35:42<4:54:30,  4.96it/s]{'loss': '1.211', 'grad_norm': '1.149', 'learning_rate': '3.908e-05', 'epoch': '21.86'}
+
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+                                                          
+
+ 22%|██▏       | 24600/112100 [1:36:01<4:00:16,  6.07it/s]{'loss': '1.214', 'grad_norm': '1.307', 'learning_rate': '3.903e-05', 'epoch': '21.95'}
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+                                                          
+
+ 22%|██▏       | 24700/112100 [1:36:25<4:18:54,  5.63it/s]{'loss': '1.214', 'grad_norm': '1.232', 'learning_rate': '3.899e-05', 'epoch': '22.03'}
+
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+                                                          
+
+ 22%|██▏       | 24800/112100 [1:36:46<5:00:47,  4.84it/s]{'loss': '1.21', 'grad_norm': '1.066', 'learning_rate': '3.894e-05', 'epoch': '22.12'}
+
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+                                                          
+
+ 22%|██▏       | 24900/112100 [1:37:07<4:33:32,  5.31it/s]{'loss': '1.212', 'grad_norm': '1.237', 'learning_rate': '3.89e-05', 'epoch': '22.21'}
+
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+                                                          
+
+ 22%|██▏       | 25000/112100 [1:37:29<4:58:23,  4.87it/s]{'loss': '1.211', 'grad_norm': '1.312', 'learning_rate': '3.885e-05', 'epoch': '22.3'}
+
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+                                                          
+
+ 22%|██▏       | 25100/112100 [1:37:50<4:08:17,  5.84it/s]{'loss': '1.211', 'grad_norm': '1.549', 'learning_rate': '3.881e-05', 'epoch': '22.39'}
+
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+                                                          
+
+ 22%|██▏       | 25200/112100 [1:38:14<4:58:56,  4.84it/s]{'loss': '1.212', 'grad_norm': '1.325', 'learning_rate': '3.876e-05', 'epoch': '22.48'}
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+                                                          
+
+ 23%|██▎       | 25300/112100 [1:38:36<5:26:01,  4.44it/s]{'loss': '1.211', 'grad_norm': '1.158', 'learning_rate': '3.872e-05', 'epoch': '22.57'}
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+                                                          
+
+ 23%|██▎       | 25400/112100 [1:39:00<4:40:46,  5.15it/s]{'loss': '1.213', 'grad_norm': '1.45', 'learning_rate': '3.868e-05', 'epoch': '22.66'}
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+                                                          
+
+ 23%|██▎       | 25500/112100 [1:39:23<5:08:02,  4.69it/s]{'loss': '1.214', 'grad_norm': '1.336', 'learning_rate': '3.863e-05', 'epoch': '22.75'}
+
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+                                                          
+
+ 23%|██▎       | 25600/112100 [1:39:47<5:07:42,  4.69it/s]{'loss': '1.212', 'grad_norm': '1.412', 'learning_rate': '3.859e-05', 'epoch': '22.84'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.211', 'grad_norm': '1.397', 'learning_rate': '3.854e-05', 'epoch': '22.93'}
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+                                                          
+
+ 23%|██▎       | 25900/112100 [1:41:06<4:57:09,  4.83it/s]{'loss': '1.212', 'grad_norm': '1.248', 'learning_rate': '3.845e-05', 'epoch': '23.1'}
+
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+                                                          
+
+ 23%|██▎       | 26000/112100 [1:41:30<5:42:41,  4.19it/s]{'loss': '1.211', 'grad_norm': '1.242', 'learning_rate': '3.841e-05', 'epoch': '23.19'}
+
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+                                                          
+
+ 23%|██▎       | 26100/112100 [1:41:55<4:37:55,  5.16it/s]{'loss': '1.212', 'grad_norm': '1.166', 'learning_rate': '3.836e-05', 'epoch': '23.28'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.212', 'grad_norm': '1.12', 'learning_rate': '3.832e-05', 'epoch': '23.37'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
+
+ 23%|██▎       | 26300/112100 [1:42:45<4:47:06,  4.98it/s]{'loss': '1.212', 'grad_norm': '1.386', 'learning_rate': '3.827e-05', 'epoch': '23.46'}
+
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+                                                          
+
+ 24%|██▎       | 26400/112100 [1:43:11<5:35:06,  4.26it/s]{'loss': '1.212', 'grad_norm': '1.131', 'learning_rate': '3.823e-05', 'epoch': '23.55'}
+
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+                                                          
+
+ 24%|██▎       | 26500/112100 [1:43:35<5:53:46,  4.03it/s]{'loss': '1.212', 'grad_norm': '1.59', 'learning_rate': '3.819e-05', 'epoch': '23.64'}
+
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+                                                          
+
+ 24%|██▎       | 26600/112100 [1:44:01<5:36:08,  4.24it/s]{'loss': '1.212', 'grad_norm': '1.358', 'learning_rate': '3.814e-05', 'epoch': '23.73'}
+
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.211', 'grad_norm': '1.312', 'learning_rate': '3.81e-05', 'epoch': '23.82'}
+
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+                                                          
+
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+
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+                                                          
+
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.21', 'grad_norm': '0.9935', 'learning_rate': '3.796e-05', 'epoch': '24.09'}
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+                                                          
+
+ 24%|██▍       | 27100/112100 [1:46:08<5:57:00,  3.97it/s]{'loss': '1.211', 'grad_norm': '1.389', 'learning_rate': '3.792e-05', 'epoch': '24.17'}
+
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+                                                          
+
+ 24%|██▍       | 27200/112100 [1:46:31<5:53:30,  4.00it/s]{'loss': '1.211', 'grad_norm': '1.342', 'learning_rate': '3.787e-05', 'epoch': '24.26'}
+
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+                                                          
+
+ 24%|██▍       | 27300/112100 [1:46:57<6:01:20,  3.91it/s]{'loss': '1.21', 'grad_norm': '1.197', 'learning_rate': '3.783e-05', 'epoch': '24.35'}
+
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+                                                          
+
+ 24%|██▍       | 27400/112100 [1:47:21<5:56:11,  3.96it/s]{'loss': '1.211', 'grad_norm': '1.44', 'learning_rate': '3.778e-05', 'epoch': '24.44'}
+
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+                                                          
+
+ 25%|██▍       | 27500/112100 [1:47:46<5:23:57,  4.35it/s]{'loss': '1.209', 'grad_norm': '2.46', 'learning_rate': '3.774e-05', 'epoch': '24.53'}
+
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+                                                          
+
+ 25%|██▍       | 27600/112100 [1:48:10<5:32:37,  4.23it/s]{'loss': '1.211', 'grad_norm': '1.07', 'learning_rate': '3.769e-05', 'epoch': '24.62'}
+
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+                                                          
+
+ 25%|██▍       | 27700/112100 [1:48:35<4:26:46,  5.27it/s]{'loss': '1.209', 'grad_norm': '1.443', 'learning_rate': '3.765e-05', 'epoch': '24.71'}
+
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+                                                          
+
+ 25%|██▍       | 27800/112100 [1:49:01<5:36:12,  4.18it/s]{'loss': '1.211', 'grad_norm': '1.561', 'learning_rate': '3.761e-05', 'epoch': '24.8'}
+
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+                                                          
+
+ 25%|██▍       | 27900/112100 [1:49:25<4:43:23,  4.95it/s]{'loss': '1.211', 'grad_norm': '1.364', 'learning_rate': '3.756e-05', 'epoch': '24.89'}
+
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+                                                          
+
+ 25%|██▍       | 28000/112100 [1:49:52<5:55:49,  3.94it/s]{'loss': '1.212', 'grad_norm': '1.211', 'learning_rate': '3.752e-05', 'epoch': '24.98'}
+
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+                                                          
+
+ 25%|██▌       | 28100/112100 [1:50:18<5:30:36,  4.23it/s]{'loss': '1.209', 'grad_norm': '1.127', 'learning_rate': '3.747e-05', 'epoch': '25.07'}
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+                                                          
+
+ 25%|██▌       | 28200/112100 [1:50:44<4:40:14,  4.99it/s]{'loss': '1.211', 'grad_norm': '1.519', 'learning_rate': '3.743e-05', 'epoch': '25.16'}
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+                                                          
+
+ 25%|██▌       | 28300/112100 [1:51:08<5:01:21,  4.63it/s]{'loss': '1.211', 'grad_norm': '1.23', 'learning_rate': '3.738e-05', 'epoch': '25.25'}
+
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+                                                          
+
+ 25%|██▌       | 28400/112100 [1:51:34<4:41:14,  4.96it/s]{'loss': '1.21', 'grad_norm': '1.388', 'learning_rate': '3.734e-05', 'epoch': '25.33'}
+
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+                                                          
+
+ 25%|██▌       | 28500/112100 [1:52:02<6:41:36,  3.47it/s]{'loss': '1.211', 'grad_norm': '1.167', 'learning_rate': '3.729e-05', 'epoch': '25.42'}
+
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+                                                          
+
+ 26%|██▌       | 28600/112100 [1:52:33<6:10:06,  3.76it/s]{'loss': '1.21', 'grad_norm': '1.24', 'learning_rate': '3.725e-05', 'epoch': '25.51'}
+
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+                                                          
+
+ 26%|██▌       | 28700/112100 [1:53:03<6:37:01,  3.50it/s]{'loss': '1.21', 'grad_norm': '1.314', 'learning_rate': '3.72e-05', 'epoch': '25.6'}
+
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+                                                          
+
+ 26%|██▌       | 28800/112100 [1:53:33<5:53:52,  3.92it/s]{'loss': '1.21', 'grad_norm': '1.786', 'learning_rate': '3.716e-05', 'epoch': '25.69'}
+
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+                                                          
+
+ 26%|██▌       | 28900/112100 [1:54:04<6:51:17,  3.37it/s]{'loss': '1.211', 'grad_norm': '1.262', 'learning_rate': '3.712e-05', 'epoch': '25.78'}
+
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.209', 'grad_norm': '1.407', 'learning_rate': '3.703e-05', 'epoch': '25.96'}
+
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+                                                          
+
+ 26%|██▌       | 29200/112100 [1:55:37<6:39:30,  3.46it/s]{'loss': '1.21', 'grad_norm': '1.082', 'learning_rate': '3.698e-05', 'epoch': '26.05'}
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+                                                          
+
+ 26%|██▌       | 29300/112100 [1:56:06<5:05:27,  4.52it/s]{'loss': '1.211', 'grad_norm': '1.331', 'learning_rate': '3.694e-05', 'epoch': '26.14'}
+
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+                                                          
+
+ 26%|██▌       | 29400/112100 [1:56:32<4:35:35,  5.00it/s]{'loss': '1.211', 'grad_norm': '1.184', 'learning_rate': '3.689e-05', 'epoch': '26.23'}
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+                                                          
+
+ 26%|██▋       | 29500/112100 [1:57:01<6:34:25,  3.49it/s]{'loss': '1.21', 'grad_norm': '1.431', 'learning_rate': '3.685e-05', 'epoch': '26.32'}
+
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+                                                          
+
+ 26%|██▋       | 29600/112100 [1:57:31<6:04:49,  3.77it/s]{'loss': '1.21', 'grad_norm': '1.095', 'learning_rate': '3.68e-05', 'epoch': '26.41'}
+
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+                                                          
+
+ 26%|██▋       | 29700/112100 [1:58:02<6:37:40,  3.45it/s]{'loss': '1.21', 'grad_norm': '1.315', 'learning_rate': '3.676e-05', 'epoch': '26.49'}
+
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+                                                          
+
+ 27%|██▋       | 29800/112100 [1:58:32<5:11:03,  4.41it/s]{'loss': '1.209', 'grad_norm': '1.801', 'learning_rate': '3.671e-05', 'epoch': '26.58'}
+
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+                                                          
+
+ 27%|██▋       | 29900/112100 [1:59:04<6:11:36,  3.69it/s]{'loss': '1.209', 'grad_norm': '1.094', 'learning_rate': '3.667e-05', 'epoch': '26.67'}
+
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+                                                          
+
+ 27%|██▋       | 30000/112100 [1:59:34<6:30:03,  3.51it/s]{'loss': '1.21', 'grad_norm': '1.335', 'learning_rate': '3.662e-05', 'epoch': '26.76'}
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+                                                          
+
+ 27%|██▋       | 30100/112100 [2:00:06<6:33:34,  3.47it/s]{'loss': '1.211', 'grad_norm': '1.38', 'learning_rate': '3.658e-05', 'epoch': '26.85'}
+
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.209', 'grad_norm': '1.518', 'learning_rate': '3.649e-05', 'epoch': '27.03'}
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+                                                          
+
+ 27%|██▋       | 30400/112100 [2:01:33<6:48:54,  3.33it/s]{'loss': '1.21', 'grad_norm': '1.266', 'learning_rate': '3.645e-05', 'epoch': '27.12'}
+
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+                                                          
+
+ 27%|██▋       | 30500/112100 [2:02:04<6:24:07,  3.54it/s]{'loss': '1.209', 'grad_norm': '1.122', 'learning_rate': '3.64e-05', 'epoch': '27.21'}
+
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.21', 'grad_norm': '1.43', 'learning_rate': '3.636e-05', 'epoch': '27.3'}
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+                                                          
+
+ 27%|██▋       | 30700/112100 [2:03:05<6:51:21,  3.30it/s]{'loss': '1.21', 'grad_norm': '1.009', 'learning_rate': '3.631e-05', 'epoch': '27.39'}
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+                                                          
+
+ 27%|██▋       | 30800/112100 [2:03:36<6:44:46,  3.35it/s]{'loss': '1.21', 'grad_norm': '1.373', 'learning_rate': '3.627e-05', 'epoch': '27.48'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                          
+
+ 28%|██▊       | 30900/112100 [2:04:07<6:30:24,  3.47it/s]{'loss': '1.21', 'grad_norm': '1.194', 'learning_rate': '3.622e-05', 'epoch': '27.56'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 28%|██▊       | 31000/112100 [2:04:37<6:39:31,  3.38it/s]{'loss': '1.207', 'grad_norm': '1.14', 'learning_rate': '3.618e-05', 'epoch': '27.65'}
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+                                                          
+
+ 28%|██▊       | 31100/112100 [2:05:08<5:45:42,  3.91it/s]{'loss': '1.21', 'grad_norm': '1.291', 'learning_rate': '3.613e-05', 'epoch': '27.74'}
+
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+                                                          
+
+ 28%|██▊       | 31200/112100 [2:05:38<6:43:21,  3.34it/s]{'loss': '1.211', 'grad_norm': '1.412', 'learning_rate': '3.609e-05', 'epoch': '27.83'}
+
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+                                                          
+
+ 28%|██▊       | 31300/112100 [2:06:04<4:50:47,  4.63it/s]{'loss': '1.209', 'grad_norm': '1.429', 'learning_rate': '3.605e-05', 'epoch': '27.92'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                          
+
+ 28%|██▊       | 31400/112100 [2:06:36<7:06:19,  3.15it/s]{'loss': '1.208', 'grad_norm': '1.059', 'learning_rate': '3.6e-05', 'epoch': '28.01'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                          
+
+ 28%|██▊       | 31500/112100 [2:07:06<6:08:12,  3.65it/s]{'loss': '1.209', 'grad_norm': '1.379', 'learning_rate': '3.596e-05', 'epoch': '28.1'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                          
+
+ 28%|██▊       | 31600/112100 [2:07:37<6:45:27,  3.31it/s]{'loss': '1.208', 'grad_norm': '1.037', 'learning_rate': '3.591e-05', 'epoch': '28.19'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
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+                                                          
+
+ 28%|██▊       | 31700/112100 [2:08:07<6:03:24,  3.69it/s]{'loss': '1.209', 'grad_norm': '1.396', 'learning_rate': '3.587e-05', 'epoch': '28.28'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
+ 28%|██▊       | 31800/112100 [2:08:38<6:41:50,  3.33it/s]{'loss': '1.21', 'grad_norm': '1.222', 'learning_rate': '3.582e-05', 'epoch': '28.37'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 28%|██▊       | 31900/112100 [2:09:07<6:08:47,  3.62it/s]{'loss': '1.209', 'grad_norm': '1.363', 'learning_rate': '3.578e-05', 'epoch': '28.46'}
+
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+                                                          
+
+ 29%|██▊       | 32000/112100 [2:09:39<6:35:18,  3.38it/s]{'loss': '1.208', 'grad_norm': '1.459', 'learning_rate': '3.573e-05', 'epoch': '28.55'}
+
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+                                                          
+
+ 29%|██▊       | 32100/112100 [2:10:09<6:35:47,  3.37it/s]{'loss': '1.209', 'grad_norm': '1.11', 'learning_rate': '3.569e-05', 'epoch': '28.64'}
+
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+                                                          
+
+ 29%|██▊       | 32200/112100 [2:10:39<5:22:30,  4.13it/s]{'loss': '1.208', 'grad_norm': '1.064', 'learning_rate': '3.564e-05', 'epoch': '28.72'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
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+                                                          
+
+ 29%|██▉       | 32300/112100 [2:11:04<6:25:24,  3.45it/s]{'loss': '1.21', 'grad_norm': '1.265', 'learning_rate': '3.56e-05', 'epoch': '28.81'}
+
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+                                                          
+
+ 29%|██▉       | 32400/112100 [2:11:35<6:26:33,  3.44it/s]{'loss': '1.21', 'grad_norm': '1.288', 'learning_rate': '3.555e-05', 'epoch': '28.9'}
+
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+                                                          
+
+ 29%|██▉       | 32500/112100 [2:12:05<6:31:25,  3.39it/s]{'loss': '1.207', 'grad_norm': '1.179', 'learning_rate': '3.551e-05', 'epoch': '28.99'}
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+                                                          
+
+ 29%|██▉       | 32600/112100 [2:12:38<6:31:38,  3.38it/s]{'loss': '1.21', 'grad_norm': '1.169', 'learning_rate': '3.547e-05', 'epoch': '29.08'}
+
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+                                                          
+
+ 29%|██▉       | 32700/112100 [2:13:08<6:35:44,  3.34it/s]{'loss': '1.208', 'grad_norm': '1.757', 'learning_rate': '3.542e-05', 'epoch': '29.17'}
+
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+                                                          
+
+ 29%|██▉       | 32800/112100 [2:13:39<6:34:42,  3.35it/s]{'loss': '1.209', 'grad_norm': '1.323', 'learning_rate': '3.538e-05', 'epoch': '29.26'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
+ 29%|██▉       | 32900/112100 [2:14:09<6:33:35,  3.35it/s]{'loss': '1.208', 'grad_norm': '1.165', 'learning_rate': '3.533e-05', 'epoch': '29.35'}
+
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+                                                          
+
+ 29%|██▉       | 33000/112100 [2:14:40<5:59:46,  3.66it/s]{'loss': '1.207', 'grad_norm': '1.445', 'learning_rate': '3.529e-05', 'epoch': '29.44'}
+
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+                                                          
+
+ 30%|██▉       | 33100/112100 [2:15:11<6:40:55,  3.28it/s]{'loss': '1.209', 'grad_norm': '1.253', 'learning_rate': '3.524e-05', 'epoch': '29.53'}
+
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+                                                          
+
+ 30%|██▉       | 33200/112100 [2:15:37<4:27:32,  4.92it/s]{'loss': '1.208', 'grad_norm': '2.246', 'learning_rate': '3.52e-05', 'epoch': '29.62'}
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.21', 'grad_norm': '1.532', 'learning_rate': '3.515e-05', 'epoch': '29.71'}
+
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+                                                          
+
+ 30%|██▉       | 33400/112100 [2:16:36<5:49:01,  3.76it/s]{'loss': '1.209', 'grad_norm': '1.442', 'learning_rate': '3.511e-05', 'epoch': '29.8'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.209', 'grad_norm': '1.542', 'learning_rate': '3.506e-05', 'epoch': '29.88'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
+
+ 30%|██▉       | 33600/112100 [2:17:38<5:57:24,  3.66it/s]{'loss': '1.21', 'grad_norm': '1.297', 'learning_rate': '3.502e-05', 'epoch': '29.97'}
+
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+                                                          
+
+ 30%|███       | 33700/112100 [2:18:11<6:18:32,  3.45it/s]{'loss': '1.208', 'grad_norm': '1.467', 'learning_rate': '3.498e-05', 'epoch': '30.06'}
+
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+                                                          
+
+ 30%|███       | 33800/112100 [2:18:41<6:21:19,  3.42it/s]{'loss': '1.208', 'grad_norm': '1.089', 'learning_rate': '3.493e-05', 'epoch': '30.15'}
+
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+                                                          
+
+ 30%|███       | 33900/112100 [2:19:12<6:26:35,  3.37it/s]{'loss': '1.207', 'grad_norm': '1.197', 'learning_rate': '3.489e-05', 'epoch': '30.24'}
+
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+                                                          
+
+ 30%|███       | 34000/112100 [2:19:42<6:20:50,  3.42it/s]{'loss': '1.209', 'grad_norm': '1.242', 'learning_rate': '3.484e-05', 'epoch': '30.33'}
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.208', 'grad_norm': '1.142', 'learning_rate': '3.48e-05', 'epoch': '30.42'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 31%|███       | 34200/112100 [2:20:37<5:11:58,  4.16it/s]{'loss': '1.208', 'grad_norm': '1.464', 'learning_rate': '3.475e-05', 'epoch': '30.51'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 31%|███       | 34300/112100 [2:21:09<6:27:09,  3.35it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.209', 'grad_norm': '1.147', 'learning_rate': '3.471e-05', 'epoch': '30.6'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 31%|███       | 34400/112100 [2:21:39<6:29:36,  3.32it/s]{'loss': '1.209', 'grad_norm': '1.136', 'learning_rate': '3.466e-05', 'epoch': '30.69'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 31%|███       | 34500/112100 [2:22:10<5:58:24,  3.61it/s]{'loss': '1.208', 'grad_norm': '1.334', 'learning_rate': '3.462e-05', 'epoch': '30.78'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
+
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+                                                          
+
+ 31%|███       | 34600/112100 [2:22:40<6:22:23,  3.38it/s]{'loss': '1.209', 'grad_norm': '1.223', 'learning_rate': '3.457e-05', 'epoch': '30.87'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 31%|███       | 34700/112100 [2:23:11<5:48:40,  3.70it/s]{'loss': '1.209', 'grad_norm': '1.302', 'learning_rate': '3.453e-05', 'epoch': '30.95'}
+
+
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+
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+                                                          
+
+ 31%|███       | 34800/112100 [2:23:43<6:26:58,  3.33it/s]{'loss': '1.208', 'grad_norm': '1.261', 'learning_rate': '3.448e-05', 'epoch': '31.04'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
+
+ 31%|███       | 34900/112100 [2:24:13<5:45:04,  3.73it/s]{'loss': '1.208', 'grad_norm': '1.39', 'learning_rate': '3.444e-05', 'epoch': '31.13'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  2.46it/s]
+
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+                                                          
+
+ 31%|███       | 35000/112100 [2:24:43<6:30:12,  3.29it/s]{'loss': '1.207', 'grad_norm': '1.191', 'learning_rate': '3.44e-05', 'epoch': '31.22'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 31%|███▏      | 35100/112100 [2:25:11<4:30:36,  4.74it/s]{'loss': '1.207', 'grad_norm': '1.335', 'learning_rate': '3.435e-05', 'epoch': '31.31'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                          
+
+ 31%|███▏      | 35200/112100 [2:25:36<5:11:47,  4.11it/s]{'loss': '1.207', 'grad_norm': '1.237', 'learning_rate': '3.431e-05', 'epoch': '31.4'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 31%|███▏      | 35300/112100 [2:26:05<5:36:25,  3.80it/s]{'loss': '1.209', 'grad_norm': '1.365', 'learning_rate': '3.426e-05', 'epoch': '31.49'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                          
+
+ 32%|███▏      | 35400/112100 [2:26:36<6:03:07,  3.52it/s]{'loss': '1.208', 'grad_norm': '1.252', 'learning_rate': '3.422e-05', 'epoch': '31.58'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 32%|███▏      | 35500/112100 [2:27:05<5:14:44,  4.06it/s]{'loss': '1.209', 'grad_norm': '1.281', 'learning_rate': '3.417e-05', 'epoch': '31.67'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 32%|███▏      | 35600/112100 [2:27:36<5:53:08,  3.61it/s]{'loss': '1.207', 'grad_norm': '1.732', 'learning_rate': '3.413e-05', 'epoch': '31.76'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 32%|███▏      | 35700/112100 [2:28:07<5:40:21,  3.74it/s]{'loss': '1.207', 'grad_norm': '1.375', 'learning_rate': '3.408e-05', 'epoch': '31.85'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 32%|███▏      | 35800/112100 [2:28:37<6:05:29,  3.48it/s]{'loss': '1.207', 'grad_norm': '1.342', 'learning_rate': '3.404e-05', 'epoch': '31.94'}
+
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+
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+                                                          
+
+ 32%|███▏      | 35900/112100 [2:29:09<5:24:15,  3.92it/s]{'loss': '1.207', 'grad_norm': '1.201', 'learning_rate': '3.399e-05', 'epoch': '32.02'}
+
+
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+                                                          
+
+ 32%|███▏      | 36000/112100 [2:29:40<5:21:18,  3.95it/s]{'loss': '1.207', 'grad_norm': '1.241', 'learning_rate': '3.395e-05', 'epoch': '32.11'}
+
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+                                                          
+
+ 32%|███▏      | 36100/112100 [2:30:08<3:44:31,  5.64it/s]{'loss': '1.207', 'grad_norm': '1.379', 'learning_rate': '3.391e-05', 'epoch': '32.2'}
+
+
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+                                                          
+
+ 32%|███▏      | 36200/112100 [2:30:34<4:43:02,  4.47it/s]{'loss': '1.206', 'grad_norm': '1.559', 'learning_rate': '3.386e-05', 'epoch': '32.29'}
+
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+                                                          
+
+ 32%|███▏      | 36300/112100 [2:31:04<6:09:53,  3.42it/s]{'loss': '1.208', 'grad_norm': '1.525', 'learning_rate': '3.382e-05', 'epoch': '32.38'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 32%|███▏      | 36400/112100 [2:31:35<6:05:34,  3.45it/s]{'loss': '1.209', 'grad_norm': '1.543', 'learning_rate': '3.377e-05', 'epoch': '32.47'}
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.206', 'grad_norm': '1.362', 'learning_rate': '3.373e-05', 'epoch': '32.56'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 33%|███▎      | 36600/112100 [2:32:34<5:42:43,  3.67it/s]{'loss': '1.206', 'grad_norm': '1.324', 'learning_rate': '3.368e-05', 'epoch': '32.65'}
+
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+                                                          
+
+ 33%|███▎      | 36700/112100 [2:33:02<5:44:51,  3.64it/s]{'loss': '1.206', 'grad_norm': '1.396', 'learning_rate': '3.364e-05', 'epoch': '32.74'}
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.207', 'grad_norm': '0.9953', 'learning_rate': '3.359e-05', 'epoch': '32.83'}
+
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+                                                          
+
+ 33%|███▎      | 36900/112100 [2:34:01<5:42:21,  3.66it/s]{'loss': '1.209', 'grad_norm': '1.343', 'learning_rate': '3.355e-05', 'epoch': '32.92'}
+
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+                                                          
+
+ 33%|███▎      | 37000/112100 [2:34:33<7:25:35,  2.81it/s]{'loss': '1.209', 'grad_norm': '1.321', 'learning_rate': '3.35e-05', 'epoch': '33.01'}
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+                                                          
+
+ 33%|███▎      | 37100/112100 [2:34:57<4:58:39,  4.19it/s]{'loss': '1.205', 'grad_norm': '1.267', 'learning_rate': '3.346e-05', 'epoch': '33.1'}
+
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+                                                          
+
+ 33%|███▎      | 37200/112100 [2:35:23<5:15:56,  3.95it/s]{'loss': '1.206', 'grad_norm': '1.133', 'learning_rate': '3.341e-05', 'epoch': '33.18'}
+
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+                                                          
+
+ 33%|███▎      | 37300/112100 [2:35:51<5:29:51,  3.78it/s]{'loss': '1.205', 'grad_norm': '1.386', 'learning_rate': '3.337e-05', 'epoch': '33.27'}
+
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+                                                          
+
+ 33%|███▎      | 37400/112100 [2:36:20<5:00:41,  4.14it/s]{'loss': '1.207', 'grad_norm': '1.628', 'learning_rate': '3.333e-05', 'epoch': '33.36'}
+
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.206', 'grad_norm': '1.081', 'learning_rate': '3.328e-05', 'epoch': '33.45'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 34%|███▎      | 37600/112100 [2:37:18<4:49:28,  4.29it/s]{'loss': '1.205', 'grad_norm': '1.155', 'learning_rate': '3.324e-05', 'epoch': '33.54'}
+
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+                                                          
+
+ 34%|███▎      | 37700/112100 [2:37:48<5:21:47,  3.85it/s]{'loss': '1.207', 'grad_norm': '1.549', 'learning_rate': '3.319e-05', 'epoch': '33.63'}
+
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+                                                          
+
+ 34%|███▎      | 37800/112100 [2:38:16<5:06:13,  4.04it/s]{'loss': '1.207', 'grad_norm': '1.49', 'learning_rate': '3.315e-05', 'epoch': '33.72'}
+
+
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+                                                          
+
+ 34%|███▍      | 37900/112100 [2:38:46<5:37:57,  3.66it/s]{'loss': '1.206', 'grad_norm': '1.287', 'learning_rate': '3.31e-05', 'epoch': '33.81'}
+
+
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.208', 'grad_norm': '1.174', 'learning_rate': '3.306e-05', 'epoch': '33.9'}
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+                                                          
+
+ 34%|███▍      | 38100/112100 [2:39:41<4:59:42,  4.12it/s]{'loss': '1.206', 'grad_norm': '1.254', 'learning_rate': '3.301e-05', 'epoch': '33.99'}
+
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+                                                          
+
+ 34%|███▍      | 38200/112100 [2:40:09<5:49:38,  3.52it/s]{'loss': '1.207', 'grad_norm': '1.262', 'learning_rate': '3.297e-05', 'epoch': '34.08'}
+
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+                                                          
+
+ 34%|███▍      | 38300/112100 [2:40:39<5:37:46,  3.64it/s]{'loss': '1.207', 'grad_norm': '1.22', 'learning_rate': '3.292e-05', 'epoch': '34.17'}
+
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+                                                          
+
+ 34%|███▍      | 38400/112100 [2:41:08<5:42:20,  3.59it/s]{'loss': '1.205', 'grad_norm': '1.214', 'learning_rate': '3.288e-05', 'epoch': '34.26'}
+
+
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+                                                          
+
+ 34%|███▍      | 38500/112100 [2:41:38<5:29:02,  3.73it/s]{'loss': '1.206', 'grad_norm': '1.347', 'learning_rate': '3.284e-05', 'epoch': '34.34'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
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+                                                          
+
+ 34%|███▍      | 38600/112100 [2:42:06<5:39:47,  3.61it/s]{'loss': '1.206', 'grad_norm': '1.145', 'learning_rate': '3.279e-05', 'epoch': '34.43'}
+
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+                                                          
+
+ 35%|███▍      | 38700/112100 [2:42:36<5:07:32,  3.98it/s]{'loss': '1.206', 'grad_norm': '1.432', 'learning_rate': '3.275e-05', 'epoch': '34.52'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                          
+
+ 35%|███▍      | 38800/112100 [2:43:05<5:42:19,  3.57it/s]{'loss': '1.205', 'grad_norm': '1.12', 'learning_rate': '3.27e-05', 'epoch': '34.61'}
+
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+                                                          
+
+ 35%|███▍      | 38900/112100 [2:43:34<5:04:28,  4.01it/s]{'loss': '1.206', 'grad_norm': '1.153', 'learning_rate': '3.266e-05', 'epoch': '34.7'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.206', 'grad_norm': '3.406', 'learning_rate': '3.261e-05', 'epoch': '34.79'}
+
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+                                                          
+
+ 35%|███▍      | 39100/112100 [2:44:25<3:51:59,  5.24it/s]{'loss': '1.206', 'grad_norm': '1.225', 'learning_rate': '3.257e-05', 'epoch': '34.88'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 35%|███▍      | 39200/112100 [2:44:54<5:34:21,  3.63it/s]{'loss': '1.208', 'grad_norm': '1.67', 'learning_rate': '3.252e-05', 'epoch': '34.97'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                          
+
+ 35%|███▌      | 39300/112100 [2:45:25<5:26:24,  3.72it/s]{'loss': '1.205', 'grad_norm': '1.339', 'learning_rate': '3.248e-05', 'epoch': '35.06'}
+
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+                                                          
+
+ 35%|███▌      | 39400/112100 [2:45:55<5:22:35,  3.76it/s]{'loss': '1.206', 'grad_norm': '1.073', 'learning_rate': '3.243e-05', 'epoch': '35.15'}
+
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+                                                          
+
+ 35%|███▌      | 39500/112100 [2:46:23<5:07:01,  3.94it/s]{'loss': '1.206', 'grad_norm': '1.394', 'learning_rate': '3.239e-05', 'epoch': '35.24'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.205', 'grad_norm': '1.39', 'learning_rate': '3.234e-05', 'epoch': '35.33'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
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+                                                          
+
+ 35%|███▌      | 39700/112100 [2:47:21<4:52:30,  4.13it/s]{'loss': '1.206', 'grad_norm': '1.354', 'learning_rate': '3.23e-05', 'epoch': '35.41'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 36%|███▌      | 39800/112100 [2:47:51<4:56:45,  4.06it/s]{'loss': '1.206', 'grad_norm': '1.674', 'learning_rate': '3.226e-05', 'epoch': '35.5'}
+
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+                                                          
+
+ 36%|███▌      | 39900/112100 [2:48:20<5:00:41,  4.00it/s]{'loss': '1.205', 'grad_norm': '1.314', 'learning_rate': '3.221e-05', 'epoch': '35.59'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 36%|███▌      | 40000/112100 [2:48:46<3:34:36,  5.60it/s]{'loss': '1.207', 'grad_norm': '1.346', 'learning_rate': '3.217e-05', 'epoch': '35.68'}
+
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+                                                          
+
+ 36%|███▌      | 40100/112100 [2:49:10<5:04:42,  3.94it/s]{'loss': '1.207', 'grad_norm': '1.368', 'learning_rate': '3.212e-05', 'epoch': '35.77'}
+
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+                                                          
+
+ 36%|███▌      | 40200/112100 [2:49:39<4:37:40,  4.32it/s]{'loss': '1.207', 'grad_norm': '1.282', 'learning_rate': '3.208e-05', 'epoch': '35.86'}
+
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+                                                          
+
+ 36%|███▌      | 40300/112100 [2:50:09<5:02:52,  3.95it/s]{'loss': '1.205', 'grad_norm': '1.418', 'learning_rate': '3.203e-05', 'epoch': '35.95'}
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.205', 'grad_norm': '1.305', 'learning_rate': '3.199e-05', 'epoch': '36.04'}
+
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+                                                          
+
+ 36%|███▌      | 40500/112100 [2:51:10<5:50:45,  3.40it/s]{'loss': '1.205', 'grad_norm': '1.589', 'learning_rate': '3.194e-05', 'epoch': '36.13'}
+
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+                                                          
+
+ 36%|███▌      | 40600/112100 [2:51:39<5:34:02,  3.57it/s]{'loss': '1.206', 'grad_norm': '1.105', 'learning_rate': '3.19e-05', 'epoch': '36.22'}
+
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+                                                          
+
+ 36%|███▋      | 40700/112100 [2:52:10<5:31:44,  3.59it/s]{'loss': '1.206', 'grad_norm': '1.422', 'learning_rate': '3.185e-05', 'epoch': '36.31'}
+
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+                                                          
+
+ 36%|███▋      | 40800/112100 [2:52:39<5:16:28,  3.75it/s]{'loss': '1.205', 'grad_norm': '1.319', 'learning_rate': '3.181e-05', 'epoch': '36.4'}
+
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+                                                          
+
+ 36%|███▋      | 40900/112100 [2:53:10<5:27:21,  3.62it/s]{'loss': '1.207', 'grad_norm': '1.295', 'learning_rate': '3.177e-05', 'epoch': '36.49'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 37%|███▋      | 41000/112100 [2:53:35<4:08:47,  4.76it/s]{'loss': '1.206', 'grad_norm': '1.33', 'learning_rate': '3.172e-05', 'epoch': '36.57'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+
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+                                                          
+
+ 37%|███▋      | 41100/112100 [2:54:03<5:22:21,  3.67it/s]{'loss': '1.205', 'grad_norm': '1.036', 'learning_rate': '3.168e-05', 'epoch': '36.66'}
+
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+                                                          
+
+ 37%|███▋      | 41200/112100 [2:54:32<5:13:09,  3.77it/s]{'loss': '1.205', 'grad_norm': '1.279', 'learning_rate': '3.163e-05', 'epoch': '36.75'}
+
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+                                                          
+
+ 37%|███▋      | 41300/112100 [2:55:03<5:16:40,  3.73it/s]{'loss': '1.206', 'grad_norm': '2.132', 'learning_rate': '3.159e-05', 'epoch': '36.84'}
+
+
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+                                                          
+
+ 37%|███▋      | 41400/112100 [2:55:33<5:37:16,  3.49it/s]{'loss': '1.205', 'grad_norm': '1.192', 'learning_rate': '3.154e-05', 'epoch': '36.93'}
+
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.206', 'grad_norm': '1.531', 'learning_rate': '3.15e-05', 'epoch': '37.02'}
+
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+                                                          
+
+ 37%|███▋      | 41600/112100 [2:56:35<5:18:53,  3.68it/s]{'loss': '1.203', 'grad_norm': '1.208', 'learning_rate': '3.145e-05', 'epoch': '37.11'}
+
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+                                                          
+
+ 37%|███▋      | 41700/112100 [2:57:04<5:05:34,  3.84it/s]{'loss': '1.204', 'grad_norm': '1.469', 'learning_rate': '3.141e-05', 'epoch': '37.2'}
+
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+                                                          
+
+ 37%|███▋      | 41800/112100 [2:57:33<5:15:11,  3.72it/s]{'loss': '1.205', 'grad_norm': '1.587', 'learning_rate': '3.136e-05', 'epoch': '37.29'}
+
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+                                                          
+
+ 37%|███▋      | 41900/112100 [2:58:04<5:32:40,  3.52it/s]{'loss': '1.207', 'grad_norm': '1.582', 'learning_rate': '3.132e-05', 'epoch': '37.38'}
+
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+                                                          
+
+ 37%|███▋      | 42000/112100 [2:58:27<4:34:11,  4.26it/s]{'loss': '1.206', 'grad_norm': '1.316', 'learning_rate': '3.127e-05', 'epoch': '37.47'}
+
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+                                                          
+
+ 38%|███▊      | 42100/112100 [2:58:56<5:43:07,  3.40it/s]{'loss': '1.206', 'grad_norm': '1.099', 'learning_rate': '3.123e-05', 'epoch': '37.56'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
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+{'loss': '1.206', 'grad_norm': '1.153', 'learning_rate': '3.119e-05', 'epoch': '37.65'}
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
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+                                                          
+
+ 38%|███▊      | 42300/112100 [2:59:56<5:24:37,  3.58it/s]{'loss': '1.205', 'grad_norm': '1.303', 'learning_rate': '3.114e-05', 'epoch': '37.73'}
+
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+                                                          
+
+ 38%|███▊      | 42400/112100 [3:00:26<5:41:52,  3.40it/s]{'loss': '1.205', 'grad_norm': '1.214', 'learning_rate': '3.11e-05', 'epoch': '37.82'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.205', 'grad_norm': '1.61', 'learning_rate': '3.105e-05', 'epoch': '37.91'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                           
+
+ 38%|███▊      | 42600/112100 [3:01:28<14:32:10,  1.33it/s]{'loss': '1.206', 'grad_norm': '1.378', 'learning_rate': '3.101e-05', 'epoch': '38'}
+
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+                                                          
+
+ 38%|███▊      | 42700/112100 [3:01:58<5:07:49,  3.76it/s]{'loss': '1.205', 'grad_norm': '0.9803', 'learning_rate': '3.096e-05', 'epoch': '38.09'}
+
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+                                                          
+
+ 38%|███▊      | 42800/112100 [3:02:27<5:39:41,  3.40it/s]{'loss': '1.204', 'grad_norm': '1.489', 'learning_rate': '3.092e-05', 'epoch': '38.18'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                          
+
+ 38%|███▊      | 42900/112100 [3:02:57<4:31:19,  4.25it/s]{'loss': '1.205', 'grad_norm': '1.346', 'learning_rate': '3.087e-05', 'epoch': '38.27'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 38%|███▊      | 43000/112100 [3:03:22<4:50:38,  3.96it/s]{'loss': '1.204', 'grad_norm': '1.231', 'learning_rate': '3.083e-05', 'epoch': '38.36'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
+ 38%|███▊      | 43100/112100 [3:03:49<5:02:58,  3.80it/s]{'loss': '1.205', 'grad_norm': '1.288', 'learning_rate': '3.078e-05', 'epoch': '38.45'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 39%|███▊      | 43200/112100 [3:04:20<5:25:55,  3.52it/s]{'loss': '1.205', 'grad_norm': '1.32', 'learning_rate': '3.074e-05', 'epoch': '38.54'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
+ 39%|███▊      | 43300/112100 [3:04:49<5:05:51,  3.75it/s]{'loss': '1.205', 'grad_norm': '0.9905', 'learning_rate': '3.07e-05', 'epoch': '38.63'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.205', 'grad_norm': '1.15', 'learning_rate': '3.065e-05', 'epoch': '38.72'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                          
+
+ 39%|███▉      | 43500/112100 [3:05:49<4:45:16,  4.01it/s]{'loss': '1.206', 'grad_norm': '1.523', 'learning_rate': '3.061e-05', 'epoch': '38.8'}
+
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+                                                          
+
+ 39%|███▉      | 43600/112100 [3:06:19<4:37:28,  4.11it/s]{'loss': '1.205', 'grad_norm': '1.07', 'learning_rate': '3.056e-05', 'epoch': '38.89'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 39%|███▉      | 43700/112100 [3:06:49<4:41:33,  4.05it/s]{'loss': '1.204', 'grad_norm': '1.16', 'learning_rate': '3.052e-05', 'epoch': '38.98'}
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+                                                          
+
+ 39%|███▉      | 43800/112100 [3:07:21<5:12:47,  3.64it/s]{'loss': '1.205', 'grad_norm': '1.385', 'learning_rate': '3.047e-05', 'epoch': '39.07'}
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.205', 'grad_norm': '1.049', 'learning_rate': '3.043e-05', 'epoch': '39.16'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                          
+
+ 39%|███▉      | 44000/112100 [3:08:16<3:39:38,  5.17it/s]{'loss': '1.204', 'grad_norm': '1.2', 'learning_rate': '3.038e-05', 'epoch': '39.25'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 39%|███▉      | 44100/112100 [3:08:43<5:13:39,  3.61it/s]{'loss': '1.204', 'grad_norm': '1.416', 'learning_rate': '3.034e-05', 'epoch': '39.34'}
+
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+                                                          
+
+ 39%|███▉      | 44200/112100 [3:09:13<4:56:18,  3.82it/s]{'loss': '1.205', 'grad_norm': '1.193', 'learning_rate': '3.029e-05', 'epoch': '39.43'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.27it/s]
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+                                                          
+
+ 40%|███▉      | 44300/112100 [3:09:43<5:26:27,  3.46it/s]{'loss': '1.204', 'grad_norm': '1.327', 'learning_rate': '3.025e-05', 'epoch': '39.52'}
+
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+                                                          
+
+ 40%|███▉      | 44400/112100 [3:10:14<4:40:42,  4.02it/s]{'loss': '1.203', 'grad_norm': '1.085', 'learning_rate': '3.021e-05', 'epoch': '39.61'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
+
+ 40%|███▉      | 44500/112100 [3:10:43<5:24:57,  3.47it/s]{'loss': '1.202', 'grad_norm': '1.276', 'learning_rate': '3.016e-05', 'epoch': '39.7'}
+
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+                                                          
+
+ 40%|███▉      | 44600/112100 [3:11:13<4:51:57,  3.85it/s]{'loss': '1.205', 'grad_norm': '1.529', 'learning_rate': '3.012e-05', 'epoch': '39.79'}
+
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+                                                          
+
+ 40%|███▉      | 44700/112100 [3:11:43<5:21:48,  3.49it/s]{'loss': '1.204', 'grad_norm': '1.145', 'learning_rate': '3.007e-05', 'epoch': '39.88'}
+
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+                                                          
+
+ 40%|███▉      | 44800/112100 [3:12:13<4:37:11,  4.05it/s]{'loss': '1.204', 'grad_norm': '1.297', 'learning_rate': '3.003e-05', 'epoch': '39.96'}
+
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+                                                          
+
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+                                                          
+
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+                                                          
+
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+                                                          
+
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.204', 'grad_norm': '1.424', 'learning_rate': '2.976e-05', 'epoch': '40.5'}
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+                                                          
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.204', 'grad_norm': '1.395', 'learning_rate': '2.967e-05', 'epoch': '40.68'}
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+                                                          
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+                                                          
+
+ 41%|████      | 45800/112100 [3:17:06<5:20:58,  3.44it/s]{'loss': '1.203', 'grad_norm': '1.108', 'learning_rate': '2.958e-05', 'epoch': '40.86'}
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+                                                          
+
+ 41%|████      | 45900/112100 [3:17:37<4:56:31,  3.72it/s]{'loss': '1.204', 'grad_norm': '1.33', 'learning_rate': '2.954e-05', 'epoch': '40.95'}
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+                                                          
+
+ 41%|████      | 46000/112100 [3:18:02<4:34:00,  4.02it/s]{'loss': '1.205', 'grad_norm': '1.18', 'learning_rate': '2.949e-05', 'epoch': '41.03'}
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+                                                          
+
+ 41%|████      | 46100/112100 [3:18:30<4:49:56,  3.79it/s]{'loss': '1.203', 'grad_norm': '1.87', 'learning_rate': '2.945e-05', 'epoch': '41.12'}
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.204', 'grad_norm': '1.199', 'learning_rate': '2.94e-05', 'epoch': '41.21'}
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+                                                          
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+ 41%|████▏     | 46300/112100 [3:19:30<4:46:17,  3.83it/s]{'loss': '1.203', 'grad_norm': '1.304', 'learning_rate': '2.936e-05', 'epoch': '41.3'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.203', 'grad_norm': '1.404', 'learning_rate': '2.931e-05', 'epoch': '41.39'}
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+                                                          
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+ 41%|████▏     | 46500/112100 [3:20:29<4:44:30,  3.84it/s]{'loss': '1.205', 'grad_norm': '1.21', 'learning_rate': '2.927e-05', 'epoch': '41.48'}
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
+
+ 42%|████▏     | 46600/112100 [3:21:00<5:20:11,  3.41it/s]{'loss': '1.204', 'grad_norm': '2.431', 'learning_rate': '2.922e-05', 'epoch': '41.57'}
+
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+                                                          
+
+ 42%|████▏     | 46700/112100 [3:21:29<4:50:53,  3.75it/s]{'loss': '1.205', 'grad_norm': '1.075', 'learning_rate': '2.918e-05', 'epoch': '41.66'}
+
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+                                                          
+
+ 42%|████▏     | 46800/112100 [3:21:59<5:11:23,  3.50it/s]{'loss': '1.203', 'grad_norm': '1.225', 'learning_rate': '2.913e-05', 'epoch': '41.75'}
+
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+                                                          
+
+ 42%|████▏     | 46900/112100 [3:22:29<4:27:51,  4.06it/s]{'loss': '1.204', 'grad_norm': '1.297', 'learning_rate': '2.909e-05', 'epoch': '41.84'}
+
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+                                                          
+
+ 42%|████▏     | 47000/112100 [3:22:55<3:43:33,  4.85it/s]{'loss': '1.204', 'grad_norm': '1.269', 'learning_rate': '2.905e-05', 'epoch': '41.93'}
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+                                                          
+
+ 42%|████▏     | 47100/112100 [3:23:26<5:20:27,  3.38it/s]{'loss': '1.204', 'grad_norm': '1.18', 'learning_rate': '2.9e-05', 'epoch': '42.02'}
+
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+                                                          
+
+ 42%|████▏     | 47200/112100 [3:23:56<5:20:28,  3.38it/s]{'loss': '1.203', 'grad_norm': '1.559', 'learning_rate': '2.896e-05', 'epoch': '42.11'}
+
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+                                                          
+
+ 42%|████▏     | 47300/112100 [3:24:25<5:19:44,  3.38it/s]{'loss': '1.204', 'grad_norm': '1.426', 'learning_rate': '2.891e-05', 'epoch': '42.19'}
+
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+                                                          
+
+ 42%|████▏     | 47400/112100 [3:24:56<5:17:01,  3.40it/s]{'loss': '1.202', 'grad_norm': '1.637', 'learning_rate': '2.887e-05', 'epoch': '42.28'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.203', 'grad_norm': '1.653', 'learning_rate': '2.882e-05', 'epoch': '42.37'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                          
+
+ 42%|████▏     | 47600/112100 [3:25:56<5:01:52,  3.56it/s]{'loss': '1.203', 'grad_norm': '0.9281', 'learning_rate': '2.878e-05', 'epoch': '42.46'}
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+                                                          
+
+ 43%|████▎     | 47700/112100 [3:26:25<5:14:41,  3.41it/s]{'loss': '1.206', 'grad_norm': '1.268', 'learning_rate': '2.873e-05', 'epoch': '42.55'}
+
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.203', 'grad_norm': '1.268', 'learning_rate': '2.869e-05', 'epoch': '42.64'}
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+                                                          
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+                                                          
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+ 43%|████▎     | 48000/112100 [3:27:47<4:14:00,  4.21it/s]{'loss': '1.204', 'grad_norm': '1.024', 'learning_rate': '2.86e-05', 'epoch': '42.82'}
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.203', 'grad_norm': '1.411', 'learning_rate': '2.856e-05', 'epoch': '42.91'}
+
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+                                                          
+
+ 43%|████▎     | 48200/112100 [3:28:47<5:13:19,  3.40it/s]{'loss': '1.203', 'grad_norm': '1.211', 'learning_rate': '2.851e-05', 'epoch': '43'}
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+                                                          
+
+ 43%|████▎     | 48300/112100 [3:29:18<5:06:07,  3.47it/s]{'loss': '1.203', 'grad_norm': '3.579', 'learning_rate': '2.847e-05', 'epoch': '43.09'}
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+                                                          
+
+ 43%|████▎     | 48400/112100 [3:29:48<4:33:26,  3.88it/s]{'loss': '1.202', 'grad_norm': '1.41', 'learning_rate': '2.842e-05', 'epoch': '43.18'}
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+                                                          
+
+ 43%|████▎     | 48500/112100 [3:30:18<4:56:08,  3.58it/s]{'loss': '1.203', 'grad_norm': '1.449', 'learning_rate': '2.838e-05', 'epoch': '43.27'}
+
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+                                                          
+
+ 43%|████▎     | 48600/112100 [3:30:48<4:38:51,  3.80it/s]{'loss': '1.202', 'grad_norm': '1.139', 'learning_rate': '2.833e-05', 'epoch': '43.35'}
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+                                                          
+
+ 43%|████▎     | 48700/112100 [3:31:18<4:58:59,  3.53it/s]{'loss': '1.204', 'grad_norm': '1.758', 'learning_rate': '2.829e-05', 'epoch': '43.44'}
+
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+                                                          
+
+ 44%|████▎     | 48800/112100 [3:31:48<4:06:04,  4.29it/s]{'loss': '1.202', 'grad_norm': '1.213', 'learning_rate': '2.824e-05', 'epoch': '43.53'}
+
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+                                                          
+
+ 44%|████▎     | 48900/112100 [3:32:16<3:47:14,  4.64it/s]{'loss': '1.202', 'grad_norm': '1.64', 'learning_rate': '2.82e-05', 'epoch': '43.62'}
+
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+                                                          
+
+ 44%|████▎     | 49000/112100 [3:32:41<4:13:01,  4.16it/s]{'loss': '1.204', 'grad_norm': '1.165', 'learning_rate': '2.815e-05', 'epoch': '43.71'}
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+                                                          
+
+ 44%|████▍     | 49100/112100 [3:33:11<4:58:52,  3.51it/s]{'loss': '1.202', 'grad_norm': '1.231', 'learning_rate': '2.811e-05', 'epoch': '43.8'}
+
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+                                                          
+
+ 44%|████▍     | 49200/112100 [3:33:40<4:01:54,  4.33it/s]{'loss': '1.203', 'grad_norm': '1.271', 'learning_rate': '2.806e-05', 'epoch': '43.89'}
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+                                                          
+
+ 44%|████▍     | 49300/112100 [3:34:11<4:52:03,  3.58it/s]{'loss': '1.205', 'grad_norm': '1.36', 'learning_rate': '2.802e-05', 'epoch': '43.98'}
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.203', 'grad_norm': '1.271', 'learning_rate': '2.798e-05', 'epoch': '44.07'}
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.203', 'grad_norm': '2.102', 'learning_rate': '2.789e-05', 'epoch': '44.25'}
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+                                                          
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+                                                          
+
+ 44%|████▍     | 49800/112100 [3:36:41<4:51:26,  3.56it/s]{'loss': '1.203', 'grad_norm': '1.396', 'learning_rate': '2.78e-05', 'epoch': '44.42'}
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+                                                          
+
+ 45%|████▍     | 49900/112100 [3:37:09<4:22:44,  3.95it/s]{'loss': '1.202', 'grad_norm': '1.228', 'learning_rate': '2.775e-05', 'epoch': '44.51'}
+
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+                                                          
+
+ 45%|████▍     | 50000/112100 [3:37:33<4:53:48,  3.52it/s]{'loss': '1.203', 'grad_norm': '1.336', 'learning_rate': '2.771e-05', 'epoch': '44.6'}
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+                                                          
+
+ 45%|████▍     | 50100/112100 [3:38:04<4:58:56,  3.46it/s]{'loss': '1.203', 'grad_norm': '1.243', 'learning_rate': '2.766e-05', 'epoch': '44.69'}
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+                                                          
+
+ 45%|████▍     | 50200/112100 [3:38:34<4:56:23,  3.48it/s]{'loss': '1.203', 'grad_norm': '1.054', 'learning_rate': '2.762e-05', 'epoch': '44.78'}
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+                                                          
+
+ 45%|████▍     | 50300/112100 [3:39:04<4:36:30,  3.73it/s]{'loss': '1.203', 'grad_norm': '1.755', 'learning_rate': '2.757e-05', 'epoch': '44.87'}
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+                                                          
+
+ 45%|████▍     | 50400/112100 [3:39:34<4:54:16,  3.49it/s]{'loss': '1.203', 'grad_norm': '1.283', 'learning_rate': '2.753e-05', 'epoch': '44.96'}
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+                                                          
+
+ 45%|████▌     | 50500/112100 [3:40:05<4:13:03,  4.06it/s]{'loss': '1.2', 'grad_norm': '0.9256', 'learning_rate': '2.748e-05', 'epoch': '45.05'}
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+                                                          
+
+ 45%|████▌     | 50600/112100 [3:40:35<4:33:43,  3.74it/s]{'loss': '1.202', 'grad_norm': '1.252', 'learning_rate': '2.744e-05', 'epoch': '45.14'}
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+                                                          
+
+ 45%|████▌     | 50700/112100 [3:41:05<4:12:41,  4.05it/s]{'loss': '1.202', 'grad_norm': '1.07', 'learning_rate': '2.74e-05', 'epoch': '45.23'}
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+                                                          
+
+ 45%|████▌     | 50800/112100 [3:41:36<5:03:24,  3.37it/s]{'loss': '1.201', 'grad_norm': '1.265', 'learning_rate': '2.735e-05', 'epoch': '45.32'}
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+                                                          
+
+ 45%|████▌     | 50900/112100 [3:42:02<3:13:15,  5.28it/s]{'loss': '1.203', 'grad_norm': '1.303', 'learning_rate': '2.731e-05', 'epoch': '45.41'}
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.203', 'grad_norm': '1.628', 'learning_rate': '2.726e-05', 'epoch': '45.5'}
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.203', 'grad_norm': '1.406', 'learning_rate': '2.717e-05', 'epoch': '45.67'}
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+                                                          
+
+ 46%|████▌     | 51300/112100 [3:43:56<4:10:07,  4.05it/s]{'loss': '1.201', 'grad_norm': '1.342', 'learning_rate': '2.713e-05', 'epoch': '45.76'}
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+                                                          
+
+ 46%|████▌     | 51400/112100 [3:44:27<4:48:42,  3.50it/s]{'loss': '1.202', 'grad_norm': '1.685', 'learning_rate': '2.708e-05', 'epoch': '45.85'}
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+                                                          
+
+ 46%|████▌     | 51500/112100 [3:44:56<4:45:27,  3.54it/s]{'loss': '1.203', 'grad_norm': '1.323', 'learning_rate': '2.704e-05', 'epoch': '45.94'}
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+                                                          
+
+ 46%|████▌     | 51600/112100 [3:45:29<4:48:50,  3.49it/s]{'loss': '1.202', 'grad_norm': '1.429', 'learning_rate': '2.699e-05', 'epoch': '46.03'}
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+                                                          
+
+ 46%|████▌     | 51700/112100 [3:45:58<4:51:43,  3.45it/s]{'loss': '1.201', 'grad_norm': '5.025', 'learning_rate': '2.695e-05', 'epoch': '46.12'}
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+                                                          
+
+ 46%|████▌     | 51800/112100 [3:46:29<4:45:56,  3.51it/s]{'loss': '1.201', 'grad_norm': '1.565', 'learning_rate': '2.691e-05', 'epoch': '46.21'}
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+                                                          
+
+ 46%|████▋     | 51900/112100 [3:46:55<4:05:28,  4.09it/s]{'loss': '1.2', 'grad_norm': '1.361', 'learning_rate': '2.686e-05', 'epoch': '46.3'}
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+                                                          
+
+ 46%|████▋     | 52000/112100 [3:47:21<4:27:34,  3.74it/s]{'loss': '1.202', 'grad_norm': '1.592', 'learning_rate': '2.682e-05', 'epoch': '46.39'}
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+                                                          
+
+ 46%|████▋     | 52100/112100 [3:47:51<4:50:15,  3.45it/s]{'loss': '1.203', 'grad_norm': '1.312', 'learning_rate': '2.677e-05', 'epoch': '46.48'}
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+                                                          
+
+ 47%|████▋     | 52200/112100 [3:48:21<4:17:50,  3.87it/s]{'loss': '1.202', 'grad_norm': '1.269', 'learning_rate': '2.673e-05', 'epoch': '46.57'}
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+                                                          
+
+ 47%|████▋     | 52300/112100 [3:48:51<4:51:40,  3.42it/s]{'loss': '1.202', 'grad_norm': '1.734', 'learning_rate': '2.668e-05', 'epoch': '46.66'}
+
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+                                                          
+
+ 47%|████▋     | 52400/112100 [3:49:21<4:19:59,  3.83it/s]{'loss': '1.202', 'grad_norm': '1.155', 'learning_rate': '2.664e-05', 'epoch': '46.74'}
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+                                                          
+
+ 47%|████▋     | 52500/112100 [3:49:50<4:30:04,  3.68it/s]{'loss': '1.202', 'grad_norm': '1.42', 'learning_rate': '2.659e-05', 'epoch': '46.83'}
+
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.202', 'grad_norm': '1.496', 'learning_rate': '2.655e-05', 'epoch': '46.92'}
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+                                                          
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+                                                          
+
+ 47%|████▋     | 52800/112100 [3:51:23<4:29:21,  3.67it/s]{'loss': '1.201', 'grad_norm': '1.592', 'learning_rate': '2.646e-05', 'epoch': '47.1'}
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+                                                          
+
+ 47%|████▋     | 52900/112100 [3:51:50<4:17:07,  3.84it/s]{'loss': '1.203', 'grad_norm': '1.385', 'learning_rate': '2.641e-05', 'epoch': '47.19'}
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+                                                          
+
+ 47%|████▋     | 53000/112100 [3:52:14<4:49:11,  3.41it/s]{'loss': '1.202', 'grad_norm': '1.279', 'learning_rate': '2.637e-05', 'epoch': '47.28'}
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+                                                          
+
+ 47%|████▋     | 53100/112100 [3:52:45<4:49:19,  3.40it/s]{'loss': '1.202', 'grad_norm': '0.9541', 'learning_rate': '2.633e-05', 'epoch': '47.37'}
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.202', 'grad_norm': '1.383', 'learning_rate': '2.624e-05', 'epoch': '47.55'}
+
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+                                                          
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+{'loss': '1.201', 'grad_norm': '1.712', 'learning_rate': '2.619e-05', 'epoch': '47.64'}
+
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+                                                          
+
+ 48%|████▊     | 53500/112100 [3:54:44<4:32:13,  3.59it/s]{'loss': '1.201', 'grad_norm': '1.133', 'learning_rate': '2.615e-05', 'epoch': '47.73'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 48%|████▊     | 53600/112100 [3:55:13<4:28:53,  3.63it/s]{'loss': '1.201', 'grad_norm': '1.435', 'learning_rate': '2.61e-05', 'epoch': '47.81'}
+
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+                                                          
+
+ 48%|████▊     | 53700/112100 [3:55:43<4:35:58,  3.53it/s]{'loss': '1.202', 'grad_norm': '2.363', 'learning_rate': '2.606e-05', 'epoch': '47.9'}
+
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+                                                          
+
+ 48%|████▊     | 53800/112100 [3:56:12<4:37:59,  3.50it/s]{'loss': '1.202', 'grad_norm': '1.252', 'learning_rate': '2.601e-05', 'epoch': '47.99'}
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+                                                          
+
+ 48%|████▊     | 53900/112100 [3:56:40<2:59:50,  5.39it/s]{'loss': '1.201', 'grad_norm': '1.171', 'learning_rate': '2.597e-05', 'epoch': '48.08'}
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+                                                          
+
+ 48%|████▊     | 54000/112100 [3:57:04<3:37:13,  4.46it/s]{'loss': '1.2', 'grad_norm': '1.25', 'learning_rate': '2.592e-05', 'epoch': '48.17'}
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+                                                          
+
+ 48%|████▊     | 54100/112100 [3:57:32<4:32:32,  3.55it/s]{'loss': '1.201', 'grad_norm': '1.58', 'learning_rate': '2.588e-05', 'epoch': '48.26'}
+
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+                                                          
+
+ 48%|████▊     | 54200/112100 [3:58:00<4:24:37,  3.65it/s]{'loss': '1.202', 'grad_norm': '1.542', 'learning_rate': '2.584e-05', 'epoch': '48.35'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.201', 'grad_norm': '1.376', 'learning_rate': '2.579e-05', 'epoch': '48.44'}
+
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.201', 'grad_norm': '1.154', 'learning_rate': '2.575e-05', 'epoch': '48.53'}
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+                                                          
+
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+
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+                                                          
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+                                                          
+
+ 49%|████▉     | 54700/112100 [4:00:26<4:31:22,  3.53it/s]{'loss': '1.201', 'grad_norm': '1.209', 'learning_rate': '2.561e-05', 'epoch': '48.8'}
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+                                                          
+
+ 49%|████▉     | 54800/112100 [4:00:55<5:03:45,  3.14it/s]{'loss': '1.202', 'grad_norm': '1.105', 'learning_rate': '2.557e-05', 'epoch': '48.89'}
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+                                                          
+
+ 49%|████▉     | 54900/112100 [4:01:20<3:13:00,  4.94it/s]{'loss': '1.203', 'grad_norm': '1.252', 'learning_rate': '2.552e-05', 'epoch': '48.97'}
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+                                                          
+
+ 49%|████▉     | 55000/112100 [4:01:47<4:25:34,  3.58it/s]{'loss': '1.201', 'grad_norm': '1.233', 'learning_rate': '2.548e-05', 'epoch': '49.06'}
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.2', 'grad_norm': '1.096', 'learning_rate': '2.539e-05', 'epoch': '49.24'}
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+                                                          
+
+ 49%|████▉     | 55300/112100 [4:03:13<4:11:57,  3.76it/s]{'loss': '1.201', 'grad_norm': '1.348', 'learning_rate': '2.535e-05', 'epoch': '49.33'}
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+                                                          
+
+ 49%|████▉     | 55400/112100 [4:03:43<4:38:02,  3.40it/s]{'loss': '1.201', 'grad_norm': '1.108', 'learning_rate': '2.53e-05', 'epoch': '49.42'}
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+                                                          
+
+ 50%|████▉     | 55500/112100 [4:04:13<4:15:49,  3.69it/s]{'loss': '1.201', 'grad_norm': '1.32', 'learning_rate': '2.526e-05', 'epoch': '49.51'}
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+                                                          
+
+ 50%|████▉     | 55600/112100 [4:04:44<4:38:44,  3.38it/s]{'loss': '1.203', 'grad_norm': '1.231', 'learning_rate': '2.521e-05', 'epoch': '49.6'}
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+                                                          
+
+ 50%|████▉     | 55700/112100 [4:05:13<3:55:40,  3.99it/s]{'loss': '1.203', 'grad_norm': '1.16', 'learning_rate': '2.517e-05', 'epoch': '49.69'}
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+                                                          
+
+ 50%|████▉     | 55800/112100 [4:05:44<4:41:01,  3.34it/s]{'loss': '1.201', 'grad_norm': '1.377', 'learning_rate': '2.512e-05', 'epoch': '49.78'}
+
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+                                                          
+
+ 50%|████▉     | 55900/112100 [4:06:08<3:09:08,  4.95it/s]{'loss': '1.201', 'grad_norm': '1.099', 'learning_rate': '2.508e-05', 'epoch': '49.87'}
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+                                                          
+
+ 50%|████▉     | 56000/112100 [4:06:36<4:24:54,  3.53it/s]{'loss': '1.2', 'grad_norm': '1.253', 'learning_rate': '2.503e-05', 'epoch': '49.96'}
+
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+                                                          
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.201', 'grad_norm': '1.359', 'learning_rate': '2.494e-05', 'epoch': '50.13'}
+
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+                                                          
+
+ 50%|█████     | 56300/112100 [4:08:07<4:17:09,  3.62it/s]{'loss': '1.201', 'grad_norm': '1.075', 'learning_rate': '2.49e-05', 'epoch': '50.22'}
+
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+                                                          
+
+ 50%|█████     | 56400/112100 [4:08:37<4:02:17,  3.83it/s]{'loss': '1.201', 'grad_norm': '1.188', 'learning_rate': '2.485e-05', 'epoch': '50.31'}
+
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+                                                          
+
+ 50%|█████     | 56500/112100 [4:09:06<4:14:25,  3.64it/s]{'loss': '1.201', 'grad_norm': '1.12', 'learning_rate': '2.481e-05', 'epoch': '50.4'}
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.201', 'grad_norm': '1.274', 'learning_rate': '2.477e-05', 'epoch': '50.49'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 51%|█████     | 56700/112100 [4:10:03<4:12:03,  3.66it/s]{'loss': '1.2', 'grad_norm': '1.31', 'learning_rate': '2.472e-05', 'epoch': '50.58'}
+
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+                                                          
+
+ 51%|█████     | 56800/112100 [4:10:33<4:09:54,  3.69it/s]{'loss': '1.201', 'grad_norm': '1.678', 'learning_rate': '2.468e-05', 'epoch': '50.67'}
+
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+                                                          
+
+ 51%|█████     | 56900/112100 [4:10:56<3:32:32,  4.33it/s]{'loss': '1.2', 'grad_norm': '1.219', 'learning_rate': '2.463e-05', 'epoch': '50.76'}
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+                                                          
+
+ 51%|█████     | 57000/112100 [4:11:22<3:47:30,  4.04it/s]{'loss': '1.2', 'grad_norm': '1.26', 'learning_rate': '2.459e-05', 'epoch': '50.85'}
+
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.202', 'grad_norm': '1.163', 'learning_rate': '2.454e-05', 'epoch': '50.94'}
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+                                                          
+
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+                                                          
+
+ 51%|█████     | 57300/112100 [4:12:50<4:10:29,  3.65it/s]{'loss': '1.2', 'grad_norm': '1.219', 'learning_rate': '2.445e-05', 'epoch': '51.12'}
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.199', 'grad_norm': '1.431', 'learning_rate': '2.441e-05', 'epoch': '51.2'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
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+                                                          
+
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+{'loss': '1.2', 'grad_norm': '1.105', 'learning_rate': '2.436e-05', 'epoch': '51.29'}
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 51%|█████▏    | 57600/112100 [4:14:16<3:40:10,  4.13it/s]{'loss': '1.2', 'grad_norm': '1.295', 'learning_rate': '2.432e-05', 'epoch': '51.38'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+
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+                                                          
+
+ 51%|█████▏    | 57700/112100 [4:14:46<4:17:36,  3.52it/s]{'loss': '1.2', 'grad_norm': '1.457', 'learning_rate': '2.428e-05', 'epoch': '51.47'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 52%|█████▏    | 57800/112100 [4:15:13<3:22:33,  4.47it/s]{'loss': '1.2', 'grad_norm': '1.093', 'learning_rate': '2.423e-05', 'epoch': '51.56'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.2', 'grad_norm': '4.731', 'learning_rate': '2.419e-05', 'epoch': '51.65'}
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+                                                          
+
+ 52%|█████▏    | 58000/112100 [4:16:05<4:00:14,  3.75it/s]{'loss': '1.201', 'grad_norm': '1.291', 'learning_rate': '2.414e-05', 'epoch': '51.74'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
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+                                                          
+
+ 52%|█████▏    | 58100/112100 [4:16:34<4:10:04,  3.60it/s]{'loss': '1.2', 'grad_norm': '1.273', 'learning_rate': '2.41e-05', 'epoch': '51.83'}
+
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+                                                          
+
+ 52%|█████▏    | 58200/112100 [4:17:02<4:11:19,  3.57it/s]{'loss': '1.2', 'grad_norm': '1.447', 'learning_rate': '2.405e-05', 'epoch': '51.92'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                          
+
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.2', 'grad_norm': '1.091', 'learning_rate': '2.396e-05', 'epoch': '52.1'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                          
+
+ 52%|█████▏    | 58500/112100 [4:18:31<3:39:13,  4.07it/s]{'loss': '1.199', 'grad_norm': '1.035', 'learning_rate': '2.392e-05', 'epoch': '52.19'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 52%|█████▏    | 58600/112100 [4:18:59<4:04:34,  3.65it/s]{'loss': '1.2', 'grad_norm': '1.567', 'learning_rate': '2.387e-05', 'epoch': '52.27'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+
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+                                                          
+
+ 52%|█████▏    | 58700/112100 [4:19:28<3:42:09,  4.01it/s]{'loss': '1.201', 'grad_norm': '1.398', 'learning_rate': '2.383e-05', 'epoch': '52.36'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.199', 'grad_norm': '1.213', 'learning_rate': '2.378e-05', 'epoch': '52.45'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+
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+                                                          
+
+ 53%|█████▎    | 58900/112100 [4:20:18<3:39:33,  4.04it/s]{'loss': '1.199', 'grad_norm': '1.782', 'learning_rate': '2.374e-05', 'epoch': '52.54'}
+
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+                                                          
+
+ 53%|█████▎    | 59000/112100 [4:20:47<4:09:00,  3.55it/s]{'loss': '1.2', 'grad_norm': '1.52', 'learning_rate': '2.37e-05', 'epoch': '52.63'}
+
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+                                                          
+
+ 53%|█████▎    | 59100/112100 [4:21:15<4:06:55,  3.58it/s]{'loss': '1.199', 'grad_norm': '1.185', 'learning_rate': '2.365e-05', 'epoch': '52.72'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.2', 'grad_norm': '1.281', 'learning_rate': '2.361e-05', 'epoch': '52.81'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                          
+
+ 53%|█████▎    | 59300/112100 [4:22:12<4:12:55,  3.48it/s]{'loss': '1.2', 'grad_norm': '1.226', 'learning_rate': '2.356e-05', 'epoch': '52.9'}
+
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+                                                          
+
+ 53%|█████▎    | 59400/112100 [4:22:42<3:58:43,  3.68it/s]{'loss': '1.2', 'grad_norm': '1.417', 'learning_rate': '2.352e-05', 'epoch': '52.99'}
+
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+                                                          
+
+ 53%|█████▎    | 59500/112100 [4:23:11<4:10:16,  3.50it/s]{'loss': '1.2', 'grad_norm': '1.096', 'learning_rate': '2.347e-05', 'epoch': '53.08'}
+
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+                                                          
+
+ 53%|█████▎    | 59600/112100 [4:23:41<4:03:23,  3.59it/s]{'loss': '1.199', 'grad_norm': '1.176', 'learning_rate': '2.343e-05', 'epoch': '53.17'}
+
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+                                                          
+
+ 53%|█████▎    | 59700/112100 [4:24:08<3:54:01,  3.73it/s]{'loss': '1.2', 'grad_norm': '1.413', 'learning_rate': '2.338e-05', 'epoch': '53.26'}
+
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+                                                          
+
+ 53%|█████▎    | 59800/112100 [4:24:32<3:12:34,  4.53it/s]{'loss': '1.2', 'grad_norm': '1.389', 'learning_rate': '2.334e-05', 'epoch': '53.35'}
+
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+
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+                                                          
+
+ 53%|█████▎    | 59900/112100 [4:24:57<3:45:06,  3.86it/s]{'loss': '1.199', 'grad_norm': '1.157', 'learning_rate': '2.329e-05', 'epoch': '53.43'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.46it/s]
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+                                                          
+
+ 54%|█████▎    | 60000/112100 [4:25:26<3:19:01,  4.36it/s]{'loss': '1.2', 'grad_norm': '1.171', 'learning_rate': '2.325e-05', 'epoch': '53.52'}
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+                                                          
+
+ 54%|█████▎    | 60100/112100 [4:25:54<4:02:50,  3.57it/s]{'loss': '1.2', 'grad_norm': '1.104', 'learning_rate': '2.321e-05', 'epoch': '53.61'}
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+                                                          
+
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.2', 'grad_norm': '1.29', 'learning_rate': '2.312e-05', 'epoch': '53.79'}
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+                                                          
+
+ 54%|█████▍    | 60400/112100 [4:27:19<4:03:20,  3.54it/s]{'loss': '1.2', 'grad_norm': '1.48', 'learning_rate': '2.307e-05', 'epoch': '53.88'}
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+                                                          
+
+ 54%|█████▍    | 60500/112100 [4:27:47<4:11:10,  3.42it/s]{'loss': '1.2', 'grad_norm': '1.578', 'learning_rate': '2.303e-05', 'epoch': '53.97'}
+
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+                                                          
+
+ 54%|█████▍    | 60600/112100 [4:28:20<4:06:03,  3.49it/s]{'loss': '1.199', 'grad_norm': '1.304', 'learning_rate': '2.298e-05', 'epoch': '54.06'}
+
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+                                                          
+
+ 54%|█████▍    | 60700/112100 [4:28:47<3:22:03,  4.24it/s]{'loss': '1.199', 'grad_norm': '1.261', 'learning_rate': '2.294e-05', 'epoch': '54.15'}
+
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+                                                          
+
+ 54%|█████▍    | 60800/112100 [4:29:12<2:51:56,  4.97it/s]{'loss': '1.199', 'grad_norm': '1.284', 'learning_rate': '2.289e-05', 'epoch': '54.24'}
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+                                                          
+
+ 54%|█████▍    | 60900/112100 [4:29:42<4:06:57,  3.46it/s]{'loss': '1.199', 'grad_norm': '1.16', 'learning_rate': '2.285e-05', 'epoch': '54.33'}
+
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+                                                          
+
+ 54%|█████▍    | 61000/112100 [4:30:12<3:42:54,  3.82it/s]{'loss': '1.2', 'grad_norm': '1.062', 'learning_rate': '2.28e-05', 'epoch': '54.42'}
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+                                                          
+
+ 55%|█████▍    | 61100/112100 [4:30:42<3:59:26,  3.55it/s]{'loss': '1.201', 'grad_norm': '1.232', 'learning_rate': '2.276e-05', 'epoch': '54.51'}
+
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+                                                          
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.2', 'grad_norm': '1.109', 'learning_rate': '2.267e-05', 'epoch': '54.68'}
+
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.198', 'grad_norm': '1.21', 'learning_rate': '2.258e-05', 'epoch': '54.86'}
+
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+                                                          
+
+ 55%|█████▍    | 61600/112100 [4:33:10<3:43:04,  3.77it/s]{'loss': '1.2', 'grad_norm': '1.242', 'learning_rate': '2.254e-05', 'epoch': '54.95'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 55%|█████▌    | 61700/112100 [4:33:41<3:08:32,  4.46it/s]{'loss': '1.198', 'grad_norm': '1.381', 'learning_rate': '2.249e-05', 'epoch': '55.04'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+
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+                                                          
+
+ 55%|█████▌    | 61800/112100 [4:34:05<3:40:05,  3.81it/s]{'loss': '1.199', 'grad_norm': '1.388', 'learning_rate': '2.245e-05', 'epoch': '55.13'}
+
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+                                                          
+
+ 55%|█████▌    | 61900/112100 [4:34:36<3:58:32,  3.51it/s]{'loss': '1.201', 'grad_norm': '1.102', 'learning_rate': '2.24e-05', 'epoch': '55.22'}
+
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+                                                          
+
+ 55%|█████▌    | 62000/112100 [4:35:05<4:04:14,  3.42it/s]{'loss': '1.2', 'grad_norm': '1.242', 'learning_rate': '2.236e-05', 'epoch': '55.31'}
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+                                                          
+
+ 55%|█████▌    | 62100/112100 [4:35:35<3:59:09,  3.48it/s]{'loss': '1.198', 'grad_norm': '1.551', 'learning_rate': '2.231e-05', 'epoch': '55.4'}
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+                                                          
+
+ 55%|█████▌    | 62200/112100 [4:36:04<3:54:07,  3.55it/s]{'loss': '1.199', 'grad_norm': '1.299', 'learning_rate': '2.227e-05', 'epoch': '55.49'}
+
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+                                                          
+
+ 56%|█████▌    | 62300/112100 [4:36:34<3:51:44,  3.58it/s]{'loss': '1.198', 'grad_norm': '1.195', 'learning_rate': '2.222e-05', 'epoch': '55.58'}
+
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+                                                          
+
+ 56%|█████▌    | 62400/112100 [4:37:03<3:47:08,  3.65it/s]{'loss': '1.198', 'grad_norm': '1.275', 'learning_rate': '2.218e-05', 'epoch': '55.66'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.198', 'grad_norm': '1.243', 'learning_rate': '2.214e-05', 'epoch': '55.75'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.40it/s]
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+                                                          
+
+ 56%|█████▌    | 62600/112100 [4:38:03<3:46:16,  3.65it/s]{'loss': '1.198', 'grad_norm': '1.221', 'learning_rate': '2.209e-05', 'epoch': '55.84'}
+
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+                                                          
+
+ 56%|█████▌    | 62700/112100 [4:38:31<2:43:59,  5.02it/s]{'loss': '1.199', 'grad_norm': '1.483', 'learning_rate': '2.205e-05', 'epoch': '55.93'}
+
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+                                                          
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.199', 'grad_norm': '1.449', 'learning_rate': '2.196e-05', 'epoch': '56.11'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
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+                                                          
+
+ 56%|█████▌    | 63000/112100 [4:39:57<3:45:21,  3.63it/s]{'loss': '1.198', 'grad_norm': '1.224', 'learning_rate': '2.191e-05', 'epoch': '56.2'}
+
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+                                                          
+
+ 56%|█████▋    | 63100/112100 [4:40:27<3:17:08,  4.14it/s]{'loss': '1.198', 'grad_norm': '1.239', 'learning_rate': '2.187e-05', 'epoch': '56.29'}
+
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+                                                          
+
+ 56%|█████▋    | 63200/112100 [4:40:58<3:51:37,  3.52it/s]{'loss': '1.198', 'grad_norm': '1.082', 'learning_rate': '2.182e-05', 'epoch': '56.38'}
+
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+                                                          
+
+ 56%|█████▋    | 63300/112100 [4:41:26<3:32:35,  3.83it/s]{'loss': '1.199', 'grad_norm': '1.056', 'learning_rate': '2.178e-05', 'epoch': '56.47'}
+
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+                                                          
+
+ 57%|█████▋    | 63400/112100 [4:41:57<3:50:19,  3.52it/s]{'loss': '1.199', 'grad_norm': '1.109', 'learning_rate': '2.173e-05', 'epoch': '56.56'}
+
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+                                                          
+
+ 57%|█████▋    | 63500/112100 [4:42:26<3:50:55,  3.51it/s]{'loss': '1.198', 'grad_norm': '1.212', 'learning_rate': '2.169e-05', 'epoch': '56.65'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+
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+                                                          
+
+ 57%|█████▋    | 63600/112100 [4:42:57<3:52:50,  3.47it/s]{'loss': '1.197', 'grad_norm': '1.045', 'learning_rate': '2.164e-05', 'epoch': '56.74'}
+
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+                                                          
+
+ 57%|█████▋    | 63700/112100 [4:43:23<3:04:12,  4.38it/s]{'loss': '1.2', 'grad_norm': '1.502', 'learning_rate': '2.16e-05', 'epoch': '56.82'}
+
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+                                                          
+
+ 57%|█████▋    | 63800/112100 [4:43:49<3:34:08,  3.76it/s]{'loss': '1.198', 'grad_norm': '1.051', 'learning_rate': '2.156e-05', 'epoch': '56.91'}
+
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+
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+                                                          
+
+ 57%|█████▋    | 63900/112100 [4:44:21<8:27:01,  1.58it/s]{'loss': '1.199', 'grad_norm': '1.714', 'learning_rate': '2.151e-05', 'epoch': '57'}
+
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+                                                          
+
+ 57%|█████▋    | 64000/112100 [4:44:52<3:35:02,  3.73it/s]{'loss': '1.198', 'grad_norm': '1.36', 'learning_rate': '2.147e-05', 'epoch': '57.09'}
+
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+                                                          
+
+ 57%|█████▋    | 64100/112100 [4:45:21<3:31:31,  3.78it/s]{'loss': '1.199', 'grad_norm': '1.309', 'learning_rate': '2.142e-05', 'epoch': '57.18'}
+
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+                                                          
+
+ 57%|█████▋    | 64200/112100 [4:45:52<3:22:30,  3.94it/s]{'loss': '1.198', 'grad_norm': '1.265', 'learning_rate': '2.138e-05', 'epoch': '57.27'}
+
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+                                                          
+
+ 57%|█████▋    | 64300/112100 [4:46:22<3:46:55,  3.51it/s]{'loss': '1.199', 'grad_norm': '1.309', 'learning_rate': '2.133e-05', 'epoch': '57.36'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.198', 'grad_norm': '1.41', 'learning_rate': '2.129e-05', 'epoch': '57.45'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.70it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.70it/s]
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.198', 'grad_norm': '1.305', 'learning_rate': '2.124e-05', 'epoch': '57.54'}
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+                                                          
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+ 58%|█████▊    | 64600/112100 [4:47:52<3:15:01,  4.06it/s]{'loss': '1.2', 'grad_norm': '1.152', 'learning_rate': '2.12e-05', 'epoch': '57.63'}
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+                                                          
+
+ 58%|█████▊    | 64700/112100 [4:48:18<2:55:44,  4.50it/s]{'loss': '1.198', 'grad_norm': '1.473', 'learning_rate': '2.115e-05', 'epoch': '57.72'}
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+                                                          
+
+ 58%|█████▊    | 64800/112100 [4:48:44<3:33:53,  3.69it/s]{'loss': '1.198', 'grad_norm': '1.59', 'learning_rate': '2.111e-05', 'epoch': '57.81'}
+
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+                                                          
+
+ 58%|█████▊    | 64900/112100 [4:49:14<3:37:51,  3.61it/s]{'loss': '1.199', 'grad_norm': '1.515', 'learning_rate': '2.107e-05', 'epoch': '57.9'}
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+                                                          
+
+ 58%|█████▊    | 65000/112100 [4:49:43<3:39:45,  3.57it/s]{'loss': '1.198', 'grad_norm': '1.316', 'learning_rate': '2.102e-05', 'epoch': '57.98'}
+
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+                                                          
+
+ 58%|█████▊    | 65100/112100 [4:50:15<3:40:59,  3.54it/s]{'loss': '1.198', 'grad_norm': '1.269', 'learning_rate': '2.098e-05', 'epoch': '58.07'}
+
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+                                                          
+
+ 58%|█████▊    | 65200/112100 [4:50:45<3:39:20,  3.56it/s]{'loss': '1.197', 'grad_norm': '1.19', 'learning_rate': '2.093e-05', 'epoch': '58.16'}
+
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+                                                          
+
+ 58%|█████▊    | 65300/112100 [4:51:15<3:41:05,  3.53it/s]{'loss': '1.199', 'grad_norm': '1.2', 'learning_rate': '2.089e-05', 'epoch': '58.25'}
+
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+                                                          
+
+ 58%|█████▊    | 65400/112100 [4:51:44<3:39:13,  3.55it/s]{'loss': '1.198', 'grad_norm': '1.317', 'learning_rate': '2.084e-05', 'epoch': '58.34'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 58%|█████▊    | 65500/112100 [4:52:14<3:38:29,  3.55it/s]{'loss': '1.199', 'grad_norm': '1.276', 'learning_rate': '2.08e-05', 'epoch': '58.43'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.43it/s]
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+                                                          
+
+ 59%|█████▊    | 65600/112100 [4:52:43<3:39:08,  3.54it/s]{'loss': '1.198', 'grad_norm': '1.203', 'learning_rate': '2.075e-05', 'epoch': '58.52'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+
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+                                                          
+
+ 59%|█████▊    | 65700/112100 [4:53:09<2:28:43,  5.20it/s]{'loss': '1.198', 'grad_norm': '1', 'learning_rate': '2.071e-05', 'epoch': '58.61'}
+
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+                                                          
+
+ 59%|█████▊    | 65800/112100 [4:53:35<3:23:07,  3.80it/s]{'loss': '1.199', 'grad_norm': '1.582', 'learning_rate': '2.066e-05', 'epoch': '58.7'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+
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+                                                          
+
+ 59%|█████▉    | 65900/112100 [4:54:06<3:07:21,  4.11it/s]{'loss': '1.198', 'grad_norm': '1.279', 'learning_rate': '2.062e-05', 'epoch': '58.79'}
+
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+                                                          
+
+ 59%|█████▉    | 66000/112100 [4:54:36<3:29:23,  3.67it/s]{'loss': '1.198', 'grad_norm': '1.772', 'learning_rate': '2.057e-05', 'epoch': '58.88'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.199', 'grad_norm': '1.147', 'learning_rate': '2.053e-05', 'epoch': '58.97'}
+
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+                                                          
+
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+                                                          
+
+ 59%|█████▉    | 66300/112100 [4:56:07<3:22:30,  3.77it/s]{'loss': '1.198', 'grad_norm': '1.976', 'learning_rate': '2.044e-05', 'epoch': '59.14'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 59%|█████▉    | 66400/112100 [4:56:37<3:17:59,  3.85it/s]{'loss': '1.198', 'grad_norm': '1.333', 'learning_rate': '2.04e-05', 'epoch': '59.23'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
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+                                                          
+
+ 59%|█████▉    | 66500/112100 [4:57:07<3:37:26,  3.50it/s]{'loss': '1.198', 'grad_norm': '1.079', 'learning_rate': '2.035e-05', 'epoch': '59.32'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 59%|█████▉    | 66600/112100 [4:57:36<3:39:30,  3.45it/s]{'loss': '1.197', 'grad_norm': '1.167', 'learning_rate': '2.031e-05', 'epoch': '59.41'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.47it/s]
+
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+                                                          
+
+ 60%|█████▉    | 66700/112100 [4:58:01<2:31:08,  5.01it/s]{'loss': '1.199', 'grad_norm': '1.251', 'learning_rate': '2.026e-05', 'epoch': '59.5'}
+
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+                                                          
+
+ 60%|█████▉    | 66800/112100 [4:58:28<3:35:14,  3.51it/s]{'loss': '1.197', 'grad_norm': '1.046', 'learning_rate': '2.022e-05', 'epoch': '59.59'}
+
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+                                                          
+
+ 60%|█████▉    | 66900/112100 [4:58:58<3:16:24,  3.84it/s]{'loss': '1.197', 'grad_norm': '1.775', 'learning_rate': '2.017e-05', 'epoch': '59.68'}
+
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+                                                          
+
+ 60%|█████▉    | 67000/112100 [4:59:28<3:32:04,  3.54it/s]{'loss': '1.198', 'grad_norm': '1.258', 'learning_rate': '2.013e-05', 'epoch': '59.77'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
+ 60%|█████▉    | 67100/112100 [4:59:58<3:21:00,  3.73it/s]{'loss': '1.198', 'grad_norm': '1.492', 'learning_rate': '2.008e-05', 'epoch': '59.86'}
+
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+                                                          
+
+ 60%|█████▉    | 67200/112100 [5:00:28<3:38:35,  3.42it/s]{'loss': '1.198', 'grad_norm': '1.188', 'learning_rate': '2.004e-05', 'epoch': '59.95'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.197', 'grad_norm': '1.142', 'learning_rate': '2e-05', 'epoch': '60.04'}
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+                                                          
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+                                                          
+
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+                                                          
+
+ 60%|██████    | 67600/112100 [5:02:29<3:13:02,  3.84it/s]{'loss': '1.198', 'grad_norm': '1.362', 'learning_rate': '1.986e-05', 'epoch': '60.3'}
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+                                                          
+
+ 60%|██████    | 67700/112100 [5:02:53<2:15:49,  5.45it/s]{'loss': '1.198', 'grad_norm': '1.352', 'learning_rate': '1.982e-05', 'epoch': '60.39'}
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+                                                          
+
+ 60%|██████    | 67800/112100 [5:03:21<3:28:25,  3.54it/s]{'loss': '1.197', 'grad_norm': '1.208', 'learning_rate': '1.977e-05', 'epoch': '60.48'}
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+                                                          
+
+ 61%|██████    | 67900/112100 [5:03:50<3:20:38,  3.67it/s]{'loss': '1.198', 'grad_norm': '1.12', 'learning_rate': '1.973e-05', 'epoch': '60.57'}
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+                                                          
+
+ 61%|██████    | 68000/112100 [5:04:21<3:21:23,  3.65it/s]{'loss': '1.198', 'grad_norm': '1.348', 'learning_rate': '1.968e-05', 'epoch': '60.66'}
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.198', 'grad_norm': '1.609', 'learning_rate': '1.959e-05', 'epoch': '60.84'}
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.197', 'grad_norm': '1.205', 'learning_rate': '1.955e-05', 'epoch': '60.93'}
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+                                                          
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.199', 'grad_norm': '1.19', 'learning_rate': '1.946e-05', 'epoch': '61.11'}
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+                                                          
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+                                                          
+
+ 61%|██████▏   | 68700/112100 [5:07:45<2:45:41,  4.37it/s]{'loss': '1.197', 'grad_norm': '1.499', 'learning_rate': '1.937e-05', 'epoch': '61.28'}
+
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+                                                          
+
+ 61%|██████▏   | 68800/112100 [5:08:12<3:02:57,  3.94it/s]{'loss': '1.197', 'grad_norm': '1.219', 'learning_rate': '1.933e-05', 'epoch': '61.37'}
+
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+                                                          
+
+ 61%|██████▏   | 68900/112100 [5:08:42<3:21:36,  3.57it/s]{'loss': '1.198', 'grad_norm': '1.118', 'learning_rate': '1.928e-05', 'epoch': '61.46'}
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+                                                          
+
+ 62%|██████▏   | 69000/112100 [5:09:12<2:58:56,  4.01it/s]{'loss': '1.198', 'grad_norm': '1.576', 'learning_rate': '1.924e-05', 'epoch': '61.55'}
+
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+                                                          
+
+ 62%|██████▏   | 69100/112100 [5:09:42<3:24:22,  3.51it/s]{'loss': '1.197', 'grad_norm': '1.52', 'learning_rate': '1.919e-05', 'epoch': '61.64'}
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+                                                          
+
+ 62%|██████▏   | 69200/112100 [5:10:11<2:55:19,  4.08it/s]{'loss': '1.199', 'grad_norm': '1.38', 'learning_rate': '1.915e-05', 'epoch': '61.73'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.39it/s]
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+                                                          
+
+ 62%|██████▏   | 69300/112100 [5:10:42<3:13:04,  3.69it/s]{'loss': '1.198', 'grad_norm': '1.192', 'learning_rate': '1.91e-05', 'epoch': '61.82'}
+
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+                                                          
+
+ 62%|██████▏   | 69400/112100 [5:11:11<2:55:39,  4.05it/s]{'loss': '1.197', 'grad_norm': '1.068', 'learning_rate': '1.906e-05', 'epoch': '61.91'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 62%|██████▏   | 69500/112100 [5:11:42<3:26:41,  3.43it/s]{'loss': '1.197', 'grad_norm': '1.072', 'learning_rate': '1.901e-05', 'epoch': '62'}
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+                                                          
+
+ 62%|██████▏   | 69600/112100 [5:12:13<3:12:41,  3.68it/s]{'loss': '1.197', 'grad_norm': '1.395', 'learning_rate': '1.897e-05', 'epoch': '62.09'}
+
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+                                                          
+
+ 62%|██████▏   | 69700/112100 [5:12:38<3:00:15,  3.92it/s]{'loss': '1.197', 'grad_norm': '1.045', 'learning_rate': '1.893e-05', 'epoch': '62.18'}
+
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+                                                          
+
+ 62%|██████▏   | 69800/112100 [5:13:03<3:23:35,  3.46it/s]{'loss': '1.197', 'grad_norm': '1.497', 'learning_rate': '1.888e-05', 'epoch': '62.27'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.63it/s]
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+                                                          
+
+ 62%|██████▏   | 69900/112100 [5:13:34<3:25:51,  3.42it/s]{'loss': '1.197', 'grad_norm': '1.434', 'learning_rate': '1.884e-05', 'epoch': '62.36'}
+
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+                                                          
+
+ 62%|██████▏   | 70000/112100 [5:14:03<3:16:00,  3.58it/s]{'loss': '1.197', 'grad_norm': '1.304', 'learning_rate': '1.879e-05', 'epoch': '62.44'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.198', 'grad_norm': '1.259', 'learning_rate': '1.875e-05', 'epoch': '62.53'}
+
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+                                                          
+
+ 63%|██████▎   | 70200/112100 [5:15:02<3:18:37,  3.52it/s]{'loss': '1.197', 'grad_norm': '1.108', 'learning_rate': '1.87e-05', 'epoch': '62.62'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                          
+
+ 63%|██████▎   | 70300/112100 [5:15:32<3:25:20,  3.39it/s]{'loss': '1.196', 'grad_norm': '1.168', 'learning_rate': '1.866e-05', 'epoch': '62.71'}
+
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+                                                          
+
+ 63%|██████▎   | 70400/112100 [5:16:01<3:22:09,  3.44it/s]{'loss': '1.197', 'grad_norm': '1.254', 'learning_rate': '1.861e-05', 'epoch': '62.8'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 63%|██████▎   | 70500/112100 [5:16:31<3:09:41,  3.65it/s]{'loss': '1.197', 'grad_norm': '1.15', 'learning_rate': '1.857e-05', 'epoch': '62.89'}
+
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+                                                          
+
+ 63%|██████▎   | 70600/112100 [5:17:01<3:18:51,  3.48it/s]{'loss': '1.199', 'grad_norm': '1.13', 'learning_rate': '1.852e-05', 'epoch': '62.98'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.67it/s]
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+                                                          
+
+ 63%|██████▎   | 70700/112100 [5:17:27<2:23:42,  4.80it/s]{'loss': '1.196', 'grad_norm': '1.458', 'learning_rate': '1.848e-05', 'epoch': '63.07'}
+
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+                                                          
+
+ 63%|██████▎   | 70800/112100 [5:17:54<3:19:57,  3.44it/s]{'loss': '1.196', 'grad_norm': '1.539', 'learning_rate': '1.843e-05', 'epoch': '63.16'}
+
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+                                                          
+
+ 63%|██████▎   | 70900/112100 [5:18:23<2:49:00,  4.06it/s]{'loss': '1.198', 'grad_norm': '1.339', 'learning_rate': '1.839e-05', 'epoch': '63.25'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.71it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.71it/s]
+
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+                                                          
+
+ 63%|██████▎   | 71000/112100 [5:18:53<3:16:17,  3.49it/s]{'loss': '1.197', 'grad_norm': '2.098', 'learning_rate': '1.835e-05', 'epoch': '63.34'}
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+                                                          
+
+ 63%|██████▎   | 71100/112100 [5:19:22<2:58:28,  3.83it/s]{'loss': '1.197', 'grad_norm': '1.172', 'learning_rate': '1.83e-05', 'epoch': '63.43'}
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+                                                          
+
+ 64%|██████▎   | 71200/112100 [5:19:52<3:14:27,  3.51it/s]{'loss': '1.197', 'grad_norm': '1.059', 'learning_rate': '1.826e-05', 'epoch': '63.51'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 64%|██████▎   | 71300/112100 [5:20:21<2:57:12,  3.84it/s]{'loss': '1.198', 'grad_norm': '1.258', 'learning_rate': '1.821e-05', 'epoch': '63.6'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
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+ 64%|██████▎   | 71400/112100 [5:20:51<3:17:16,  3.44it/s]{'loss': '1.197', 'grad_norm': '1.225', 'learning_rate': '1.817e-05', 'epoch': '63.69'}
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.198', 'grad_norm': '1.094', 'learning_rate': '1.812e-05', 'epoch': '63.78'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
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+                                                          
+
+ 64%|██████▍   | 71600/112100 [5:21:50<3:17:00,  3.43it/s]{'loss': '1.197', 'grad_norm': '1.193', 'learning_rate': '1.808e-05', 'epoch': '63.87'}
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.197', 'grad_norm': '1.513', 'learning_rate': '1.803e-05', 'epoch': '63.96'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                          
+
+ 64%|██████▍   | 71800/112100 [5:22:43<3:15:55,  3.43it/s]{'loss': '1.197', 'grad_norm': '1.011', 'learning_rate': '1.799e-05', 'epoch': '64.05'}
+
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+                                                          
+
+ 64%|██████▍   | 71900/112100 [5:23:12<3:16:16,  3.41it/s]{'loss': '1.196', 'grad_norm': '1.128', 'learning_rate': '1.794e-05', 'epoch': '64.14'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 64%|██████▍   | 72000/112100 [5:23:42<3:23:39,  3.28it/s]{'loss': '1.196', 'grad_norm': '1.058', 'learning_rate': '1.79e-05', 'epoch': '64.23'}
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+                                                          
+
+ 64%|██████▍   | 72100/112100 [5:24:10<3:14:22,  3.43it/s]{'loss': '1.197', 'grad_norm': '1.573', 'learning_rate': '1.786e-05', 'epoch': '64.32'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.196', 'grad_norm': '1.172', 'learning_rate': '1.781e-05', 'epoch': '64.41'}
+
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+                                                          
+
+ 64%|██████▍   | 72300/112100 [5:25:09<3:00:36,  3.67it/s]{'loss': '1.197', 'grad_norm': '1.162', 'learning_rate': '1.777e-05', 'epoch': '64.5'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+
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+                                                          
+
+ 65%|██████▍   | 72400/112100 [5:25:40<3:06:37,  3.55it/s]{'loss': '1.197', 'grad_norm': '1.029', 'learning_rate': '1.772e-05', 'epoch': '64.59'}
+
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+                                                          
+
+ 65%|██████▍   | 72500/112100 [5:26:09<3:07:20,  3.52it/s]{'loss': '1.197', 'grad_norm': '1.483', 'learning_rate': '1.768e-05', 'epoch': '64.67'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 65%|██████▍   | 72600/112100 [5:26:39<3:08:26,  3.49it/s]{'loss': '1.196', 'grad_norm': '1.078', 'learning_rate': '1.763e-05', 'epoch': '64.76'}
+
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+                                                          
+
+ 65%|██████▍   | 72700/112100 [5:27:03<2:12:13,  4.97it/s]{'loss': '1.197', 'grad_norm': '1.07', 'learning_rate': '1.759e-05', 'epoch': '64.85'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 65%|██████▍   | 72800/112100 [5:27:27<2:32:58,  4.28it/s]{'loss': '1.196', 'grad_norm': '1.308', 'learning_rate': '1.754e-05', 'epoch': '64.94'}
+
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+                                                          
+
+ 65%|██████▌   | 72900/112100 [5:27:59<2:54:21,  3.75it/s]{'loss': '1.196', 'grad_norm': '2.159', 'learning_rate': '1.75e-05', 'epoch': '65.03'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
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+                                                          
+
+ 65%|██████▌   | 73000/112100 [5:28:29<3:09:18,  3.44it/s]{'loss': '1.196', 'grad_norm': '1.18', 'learning_rate': '1.745e-05', 'epoch': '65.12'}
+
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+                                                          
+
+ 65%|██████▌   | 73100/112100 [5:28:58<2:52:03,  3.78it/s]{'loss': '1.195', 'grad_norm': '1.278', 'learning_rate': '1.741e-05', 'epoch': '65.21'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 65%|██████▌   | 73200/112100 [5:29:28<3:10:58,  3.39it/s]{'loss': '1.196', 'grad_norm': '1.509', 'learning_rate': '1.736e-05', 'epoch': '65.3'}
+
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+                                                          
+
+ 65%|██████▌   | 73300/112100 [5:29:57<2:47:32,  3.86it/s]{'loss': '1.196', 'grad_norm': '1.491', 'learning_rate': '1.732e-05', 'epoch': '65.39'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 65%|██████▌   | 73400/112100 [5:30:27<3:06:50,  3.45it/s]{'loss': '1.197', 'grad_norm': '1.112', 'learning_rate': '1.728e-05', 'epoch': '65.48'}
+
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+                                                          
+
+ 66%|██████▌   | 73500/112100 [5:30:56<3:07:06,  3.44it/s]{'loss': '1.197', 'grad_norm': '2.072', 'learning_rate': '1.723e-05', 'epoch': '65.57'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 66%|██████▌   | 73600/112100 [5:31:27<3:10:54,  3.36it/s]{'loss': '1.196', 'grad_norm': '1.119', 'learning_rate': '1.719e-05', 'epoch': '65.66'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 66%|██████▌   | 73700/112100 [5:31:53<2:23:25,  4.46it/s]{'loss': '1.196', 'grad_norm': '1.049', 'learning_rate': '1.714e-05', 'epoch': '65.75'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 66%|██████▌   | 73800/112100 [5:32:18<2:28:26,  4.30it/s]{'loss': '1.197', 'grad_norm': '1.163', 'learning_rate': '1.71e-05', 'epoch': '65.83'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+                                                          
+
+ 66%|██████▌   | 73900/112100 [5:32:47<2:49:33,  3.75it/s]{'loss': '1.196', 'grad_norm': '1.471', 'learning_rate': '1.705e-05', 'epoch': '65.92'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
+
+ 66%|██████▌   | 73901/112100 [5:32:49<9:03:37,  1.17it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                          
+
+ 66%|██████▌   | 74000/112100 [5:33:19<2:55:09,  3.63it/s]{'loss': '1.196', 'grad_norm': '1.639', 'learning_rate': '1.701e-05', 'epoch': '66.01'}
+
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+                                                          
+
+ 66%|██████▌   | 74100/112100 [5:33:49<2:52:47,  3.67it/s]{'loss': '1.196', 'grad_norm': '1.122', 'learning_rate': '1.696e-05', 'epoch': '66.1'}
+
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+                                                          
+
+ 66%|██████▌   | 74200/112100 [5:34:20<2:49:40,  3.72it/s]{'loss': '1.195', 'grad_norm': '1.042', 'learning_rate': '1.692e-05', 'epoch': '66.19'}
+
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+                                                          
+
+ 66%|██████▋   | 74300/112100 [5:34:49<2:56:12,  3.58it/s]{'loss': '1.196', 'grad_norm': '1.217', 'learning_rate': '1.687e-05', 'epoch': '66.28'}
+
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+                                                          
+
+ 66%|██████▋   | 74400/112100 [5:35:19<2:39:32,  3.94it/s]{'loss': '1.195', 'grad_norm': '1.379', 'learning_rate': '1.683e-05', 'epoch': '66.37'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.67it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.197', 'grad_norm': '1.153', 'learning_rate': '1.679e-05', 'epoch': '66.46'}
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+                                                          
+
+ 67%|██████▋   | 74600/112100 [5:36:19<2:45:16,  3.78it/s]{'loss': '1.197', 'grad_norm': '1.048', 'learning_rate': '1.674e-05', 'epoch': '66.55'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.196', 'grad_norm': '1.342', 'learning_rate': '1.67e-05', 'epoch': '66.64'}
+
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+                                                          
+
+ 67%|██████▋   | 74800/112100 [5:37:10<2:43:09,  3.81it/s]{'loss': '1.197', 'grad_norm': '1.211', 'learning_rate': '1.665e-05', 'epoch': '66.73'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.63it/s]
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+                                                          
+
+ 67%|██████▋   | 74900/112100 [5:37:40<2:56:39,  3.51it/s]{'loss': '1.196', 'grad_norm': '1.216', 'learning_rate': '1.661e-05', 'epoch': '66.82'}
+
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+                                                          
+
+ 67%|██████▋   | 75000/112100 [5:38:09<2:37:22,  3.93it/s]{'loss': '1.196', 'grad_norm': '1.097', 'learning_rate': '1.656e-05', 'epoch': '66.9'}
+
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+                                                          
+
+ 67%|██████▋   | 75100/112100 [5:38:40<2:54:17,  3.54it/s]{'loss': '1.196', 'grad_norm': '2.077', 'learning_rate': '1.652e-05', 'epoch': '66.99'}
+
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+                                                          
+
+ 67%|██████▋   | 75200/112100 [5:39:10<2:42:31,  3.78it/s]{'loss': '1.196', 'grad_norm': '1.967', 'learning_rate': '1.647e-05', 'epoch': '67.08'}
+
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+                                                          
+
+ 67%|██████▋   | 75300/112100 [5:39:41<2:47:37,  3.66it/s]{'loss': '1.196', 'grad_norm': '1.301', 'learning_rate': '1.643e-05', 'epoch': '67.17'}
+
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+                                                          
+
+ 67%|██████▋   | 75400/112100 [5:40:09<2:45:23,  3.70it/s]{'loss': '1.197', 'grad_norm': '1.337', 'learning_rate': '1.638e-05', 'epoch': '67.26'}
+
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+                                                          
+
+ 67%|██████▋   | 75500/112100 [5:40:40<2:46:18,  3.67it/s]{'loss': '1.196', 'grad_norm': '1.519', 'learning_rate': '1.634e-05', 'epoch': '67.35'}
+
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+                                                          
+
+ 67%|██████▋   | 75600/112100 [5:41:09<2:48:36,  3.61it/s]{'loss': '1.196', 'grad_norm': '1.328', 'learning_rate': '1.629e-05', 'epoch': '67.44'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 68%|██████▊   | 75700/112100 [5:41:36<2:12:25,  4.58it/s]{'loss': '1.197', 'grad_norm': '1.247', 'learning_rate': '1.625e-05', 'epoch': '67.53'}
+
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+                                                          
+
+ 68%|██████▊   | 75800/112100 [5:42:00<2:07:13,  4.76it/s]{'loss': '1.195', 'grad_norm': '1.229', 'learning_rate': '1.621e-05', 'epoch': '67.62'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 68%|██████▊   | 75900/112100 [5:42:30<2:35:40,  3.88it/s]{'loss': '1.195', 'grad_norm': '1.214', 'learning_rate': '1.616e-05', 'epoch': '67.71'}
+
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+                                                          
+
+ 68%|██████▊   | 76000/112100 [5:43:00<2:46:45,  3.61it/s]{'loss': '1.197', 'grad_norm': '1.229', 'learning_rate': '1.612e-05', 'epoch': '67.8'}
+
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+                                                          
+
+ 68%|██████▊   | 76100/112100 [5:43:30<2:50:18,  3.52it/s]{'loss': '1.196', 'grad_norm': '1.725', 'learning_rate': '1.607e-05', 'epoch': '67.89'}
+
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+                                                          
+
+ 68%|██████▊   | 76200/112100 [5:43:59<2:49:50,  3.52it/s]{'loss': '1.196', 'grad_norm': '1.069', 'learning_rate': '1.603e-05', 'epoch': '67.98'}
+
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+                                                          
+
+ 68%|██████▊   | 76300/112100 [5:44:31<2:31:37,  3.94it/s]{'loss': '1.195', 'grad_norm': '0.9191', 'learning_rate': '1.598e-05', 'epoch': '68.06'}
+
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+                                                          
+
+ 68%|██████▊   | 76400/112100 [5:45:01<2:52:43,  3.44it/s]{'loss': '1.195', 'grad_norm': '1.41', 'learning_rate': '1.594e-05', 'epoch': '68.15'}
+
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+                                                          
+
+ 68%|██████▊   | 76500/112100 [5:45:31<2:33:48,  3.86it/s]{'loss': '1.196', 'grad_norm': '1.153', 'learning_rate': '1.589e-05', 'epoch': '68.24'}
+
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+                                                          
+
+ 68%|██████▊   | 76600/112100 [5:46:00<2:45:15,  3.58it/s]{'loss': '1.195', 'grad_norm': '1.186', 'learning_rate': '1.585e-05', 'epoch': '68.33'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
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+                                                          
+
+ 68%|██████▊   | 76700/112100 [5:46:27<1:58:49,  4.97it/s]{'loss': '1.195', 'grad_norm': '1.247', 'learning_rate': '1.58e-05', 'epoch': '68.42'}
+
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+                                                          
+
+ 69%|██████▊   | 76800/112100 [5:46:52<2:17:32,  4.28it/s]{'loss': '1.196', 'grad_norm': '1.665', 'learning_rate': '1.576e-05', 'epoch': '68.51'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 69%|██████▊   | 76900/112100 [5:47:21<2:24:55,  4.05it/s]{'loss': '1.196', 'grad_norm': '1.006', 'learning_rate': '1.571e-05', 'epoch': '68.6'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
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+                                                          
+
+ 69%|██████▊   | 77000/112100 [5:47:51<2:45:59,  3.52it/s]{'loss': '1.196', 'grad_norm': '1.321', 'learning_rate': '1.567e-05', 'epoch': '68.69'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.196', 'grad_norm': '1.387', 'learning_rate': '1.563e-05', 'epoch': '68.78'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
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+                                                          
+
+ 69%|██████▉   | 77200/112100 [5:48:50<2:45:23,  3.52it/s]{'loss': '1.197', 'grad_norm': '1.557', 'learning_rate': '1.558e-05', 'epoch': '68.87'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.63it/s]
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+                                                          
+
+ 69%|██████▉   | 77300/112100 [5:49:19<2:27:55,  3.92it/s]{'loss': '1.196', 'grad_norm': '1.29', 'learning_rate': '1.554e-05', 'epoch': '68.96'}
+
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+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.196', 'grad_norm': '1.157', 'learning_rate': '1.549e-05', 'epoch': '69.05'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
+
+ 69%|██████▉   | 77500/112100 [5:50:20<2:28:01,  3.90it/s]{'loss': '1.194', 'grad_norm': '1.069', 'learning_rate': '1.545e-05', 'epoch': '69.13'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+                                                          
+
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+                                                          
+
+ 69%|██████▉   | 77700/112100 [5:51:17<2:16:02,  4.21it/s]{'loss': '1.196', 'grad_norm': '1.358', 'learning_rate': '1.536e-05', 'epoch': '69.31'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                          
+
+ 69%|██████▉   | 77800/112100 [5:51:43<2:15:59,  4.20it/s]{'loss': '1.195', 'grad_norm': '1.395', 'learning_rate': '1.531e-05', 'epoch': '69.4'}
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+                                                          
+
+ 69%|██████▉   | 77900/112100 [5:52:12<2:44:07,  3.47it/s]{'loss': '1.195', 'grad_norm': '1.24', 'learning_rate': '1.527e-05', 'epoch': '69.49'}
+
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+                                                          
+
+ 70%|██████▉   | 78000/112100 [5:52:42<2:37:21,  3.61it/s]{'loss': '1.195', 'grad_norm': '1.151', 'learning_rate': '1.522e-05', 'epoch': '69.58'}
+
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+                                                          
+
+ 70%|██████▉   | 78100/112100 [5:53:11<2:46:30,  3.40it/s]{'loss': '1.196', 'grad_norm': '1.479', 'learning_rate': '1.518e-05', 'epoch': '69.67'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
+
+ 70%|██████▉   | 78200/112100 [5:53:41<2:29:41,  3.77it/s]{'loss': '1.196', 'grad_norm': '1.413', 'learning_rate': '1.514e-05', 'epoch': '69.76'}
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.195', 'grad_norm': '1.236', 'learning_rate': '1.509e-05', 'epoch': '69.85'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.196', 'grad_norm': '1.162', 'learning_rate': '1.505e-05', 'epoch': '69.94'}
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+                                                          
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.196', 'grad_norm': '1.298', 'learning_rate': '1.5e-05', 'epoch': '70.03'}
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+                                                          
+
+ 70%|███████   | 78600/112100 [5:55:41<2:30:39,  3.71it/s]{'loss': '1.195', 'grad_norm': '1.231', 'learning_rate': '1.496e-05', 'epoch': '70.12'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.196', 'grad_norm': '1.436', 'learning_rate': '1.491e-05', 'epoch': '70.21'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
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+                                                          
+
+ 70%|███████   | 78800/112100 [5:56:32<1:56:56,  4.75it/s]{'loss': '1.195', 'grad_norm': '1.362', 'learning_rate': '1.487e-05', 'epoch': '70.29'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 70%|███████   | 78900/112100 [5:57:01<2:28:18,  3.73it/s]{'loss': '1.195', 'grad_norm': '1.284', 'learning_rate': '1.482e-05', 'epoch': '70.38'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.196', 'grad_norm': '1.431', 'learning_rate': '1.478e-05', 'epoch': '70.47'}
+
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+                                                          
+
+ 71%|███████   | 79100/112100 [5:58:00<2:29:54,  3.67it/s]{'loss': '1.194', 'grad_norm': '1.457', 'learning_rate': '1.473e-05', 'epoch': '70.56'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                          
+
+ 71%|███████   | 79200/112100 [5:58:30<2:17:04,  4.00it/s]{'loss': '1.196', 'grad_norm': '1.288', 'learning_rate': '1.469e-05', 'epoch': '70.65'}
+
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+                                                          
+
+ 71%|███████   | 79300/112100 [5:59:00<2:37:37,  3.47it/s]{'loss': '1.196', 'grad_norm': '1.446', 'learning_rate': '1.465e-05', 'epoch': '70.74'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 71%|███████   | 79400/112100 [5:59:30<2:22:44,  3.82it/s]{'loss': '1.196', 'grad_norm': '1.336', 'learning_rate': '1.46e-05', 'epoch': '70.83'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 71%|███████   | 79500/112100 [5:59:58<2:38:39,  3.42it/s]{'loss': '1.195', 'grad_norm': '1.365', 'learning_rate': '1.456e-05', 'epoch': '70.92'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
+
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+                                                          
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+{'loss': '1.197', 'grad_norm': '2.067', 'learning_rate': '1.451e-05', 'epoch': '71.01'}
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+                                                          
+
+ 71%|███████   | 79700/112100 [6:00:57<2:12:04,  4.09it/s]{'loss': '1.196', 'grad_norm': '1.258', 'learning_rate': '1.447e-05', 'epoch': '71.1'}
+
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+                                                          
+
+ 71%|███████   | 79800/112100 [6:01:21<1:53:26,  4.75it/s]{'loss': '1.196', 'grad_norm': '0.9868', 'learning_rate': '1.442e-05', 'epoch': '71.19'}
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+                                                          
+
+ 71%|███████▏  | 79900/112100 [6:01:51<2:32:13,  3.53it/s]{'loss': '1.195', 'grad_norm': '1.173', 'learning_rate': '1.438e-05', 'epoch': '71.28'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                          
+
+ 71%|███████▏  | 80000/112100 [6:02:20<2:21:54,  3.77it/s]{'loss': '1.195', 'grad_norm': '1.353', 'learning_rate': '1.433e-05', 'epoch': '71.37'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 71%|███████▏  | 80100/112100 [6:02:51<2:36:49,  3.40it/s]{'loss': '1.195', 'grad_norm': '1.187', 'learning_rate': '1.429e-05', 'epoch': '71.45'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
+
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+                                                          
+
+ 72%|███████▏  | 80200/112100 [6:03:20<2:30:41,  3.53it/s]{'loss': '1.195', 'grad_norm': '1.771', 'learning_rate': '1.424e-05', 'epoch': '71.54'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
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+                                                          
+
+ 72%|███████▏  | 80300/112100 [6:03:50<2:30:54,  3.51it/s]{'loss': '1.195', 'grad_norm': '1.336', 'learning_rate': '1.42e-05', 'epoch': '71.63'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
+ 72%|███████▏  | 80301/112100 [6:03:52<7:28:40,  1.18it/s]
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+                                                          
+
+ 72%|███████▏  | 80400/112100 [6:04:19<2:28:46,  3.55it/s]{'loss': '1.195', 'grad_norm': '1.197', 'learning_rate': '1.415e-05', 'epoch': '71.72'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 72%|███████▏  | 80500/112100 [6:04:49<2:26:43,  3.59it/s]{'loss': '1.195', 'grad_norm': '1.217', 'learning_rate': '1.411e-05', 'epoch': '71.81'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+
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+                                                          
+
+ 72%|███████▏  | 80600/112100 [6:05:18<2:26:17,  3.59it/s]{'loss': '1.195', 'grad_norm': '1.491', 'learning_rate': '1.407e-05', 'epoch': '71.9'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 72%|███████▏  | 80700/112100 [6:05:47<1:53:01,  4.63it/s]{'loss': '1.196', 'grad_norm': '1.606', 'learning_rate': '1.402e-05', 'epoch': '71.99'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.63it/s]
+
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+                                                          
+
+ 72%|███████▏  | 80800/112100 [6:06:13<1:41:24,  5.14it/s]{'loss': '1.195', 'grad_norm': '1.52', 'learning_rate': '1.398e-05', 'epoch': '72.08'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 72%|███████▏  | 80900/112100 [6:06:43<1:56:57,  4.45it/s]{'loss': '1.194', 'grad_norm': '1.058', 'learning_rate': '1.393e-05', 'epoch': '72.17'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
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+                                                          
+
+ 72%|███████▏  | 81000/112100 [6:07:12<2:09:34,  4.00it/s]{'loss': '1.193', 'grad_norm': '1.326', 'learning_rate': '1.389e-05', 'epoch': '72.26'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+                                                          
+
+ 72%|███████▏  | 81100/112100 [6:07:43<2:00:37,  4.28it/s]{'loss': '1.196', 'grad_norm': '1.011', 'learning_rate': '1.384e-05', 'epoch': '72.35'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
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+                                                          
+
+ 72%|███████▏  | 81200/112100 [6:08:12<2:15:24,  3.80it/s]{'loss': '1.195', 'grad_norm': '1.069', 'learning_rate': '1.38e-05', 'epoch': '72.44'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+
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+                                                          
+
+ 73%|███████▎  | 81300/112100 [6:08:42<2:00:20,  4.27it/s]{'loss': '1.195', 'grad_norm': '1.179', 'learning_rate': '1.375e-05', 'epoch': '72.52'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                          
+
+ 73%|███████▎  | 81400/112100 [6:09:11<2:19:20,  3.67it/s]{'loss': '1.194', 'grad_norm': '1.273', 'learning_rate': '1.371e-05', 'epoch': '72.61'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 73%|███████▎  | 81500/112100 [6:09:41<2:04:42,  4.09it/s]{'loss': '1.195', 'grad_norm': '1.326', 'learning_rate': '1.366e-05', 'epoch': '72.7'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 73%|███████▎  | 81600/112100 [6:10:11<2:18:08,  3.68it/s]{'loss': '1.195', 'grad_norm': '1.149', 'learning_rate': '1.362e-05', 'epoch': '72.79'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                          
+
+ 73%|███████▎  | 81700/112100 [6:10:39<1:35:14,  5.32it/s]{'loss': '1.196', 'grad_norm': '1.292', 'learning_rate': '1.357e-05', 'epoch': '72.88'}
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+                                                          
+
+ 73%|███████▎  | 81800/112100 [6:11:03<1:56:05,  4.35it/s]{'loss': '1.195', 'grad_norm': '1.238', 'learning_rate': '1.353e-05', 'epoch': '72.97'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 73%|███████▎  | 81900/112100 [6:11:32<2:09:39,  3.88it/s]{'loss': '1.194', 'grad_norm': '1.56', 'learning_rate': '1.349e-05', 'epoch': '73.06'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 73%|███████▎  | 82000/112100 [6:12:02<2:25:33,  3.45it/s]{'loss': '1.195', 'grad_norm': '1.52', 'learning_rate': '1.344e-05', 'epoch': '73.15'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+
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+                                                          
+
+ 73%|███████▎  | 82100/112100 [6:12:31<2:11:21,  3.81it/s]{'loss': '1.195', 'grad_norm': '1.21', 'learning_rate': '1.34e-05', 'epoch': '73.24'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                          
+
+ 73%|███████▎  | 82200/112100 [6:13:01<2:19:34,  3.57it/s]{'loss': '1.195', 'grad_norm': '1.036', 'learning_rate': '1.335e-05', 'epoch': '73.33'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.67it/s]
+
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+                                                          
+
+ 73%|███████▎  | 82300/112100 [6:13:30<2:11:14,  3.78it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.195', 'grad_norm': '1.237', 'learning_rate': '1.331e-05', 'epoch': '73.42'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+
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+                                                          
+
+ 74%|███████▎  | 82400/112100 [6:14:00<2:10:16,  3.80it/s]{'loss': '1.195', 'grad_norm': '1.909', 'learning_rate': '1.326e-05', 'epoch': '73.51'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+
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+                                                          
+
+ 74%|███████▎  | 82500/112100 [6:14:29<2:13:38,  3.69it/s]{'loss': '1.194', 'grad_norm': '1.03', 'learning_rate': '1.322e-05', 'epoch': '73.6'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.66it/s]
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+                                                          
+
+ 74%|███████▎  | 82600/112100 [6:14:59<2:19:35,  3.52it/s]{'loss': '1.195', 'grad_norm': '1.312', 'learning_rate': '1.317e-05', 'epoch': '73.68'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
+
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+                                                          
+
+ 74%|███████▍  | 82700/112100 [6:15:27<1:54:14,  4.29it/s]{'loss': '1.195', 'grad_norm': '1.057', 'learning_rate': '1.313e-05', 'epoch': '73.77'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 74%|███████▍  | 82800/112100 [6:15:52<1:50:15,  4.43it/s]{'loss': '1.195', 'grad_norm': '1.253', 'learning_rate': '1.308e-05', 'epoch': '73.86'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 74%|███████▍  | 82900/112100 [6:16:18<2:15:43,  3.59it/s]{'loss': '1.195', 'grad_norm': '1.282', 'learning_rate': '1.304e-05', 'epoch': '73.95'}
+
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+
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+                                                          
+
+ 74%|███████▍  | 83000/112100 [6:16:51<2:19:48,  3.47it/s]{'loss': '1.194', 'grad_norm': '1.043', 'learning_rate': '1.3e-05', 'epoch': '74.04'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
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+                                                          
+
+ 74%|███████▍  | 83100/112100 [6:17:19<2:20:16,  3.45it/s]{'loss': '1.194', 'grad_norm': '1.395', 'learning_rate': '1.295e-05', 'epoch': '74.13'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+
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+                                                          
+
+ 74%|███████▍  | 83200/112100 [6:17:50<2:17:39,  3.50it/s]{'loss': '1.195', 'grad_norm': '1.207', 'learning_rate': '1.291e-05', 'epoch': '74.22'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+
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+                                                          
+
+ 74%|███████▍  | 83300/112100 [6:18:19<2:17:54,  3.48it/s]{'loss': '1.195', 'grad_norm': '1.152', 'learning_rate': '1.286e-05', 'epoch': '74.31'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
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+                                                          
+
+ 74%|███████▍  | 83400/112100 [6:18:50<2:05:51,  3.80it/s]{'loss': '1.194', 'grad_norm': '1.085', 'learning_rate': '1.282e-05', 'epoch': '74.4'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 74%|███████▍  | 83500/112100 [6:19:19<2:19:36,  3.41it/s]{'loss': '1.194', 'grad_norm': '1.17', 'learning_rate': '1.277e-05', 'epoch': '74.49'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+
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+                                                          
+
+ 75%|███████▍  | 83600/112100 [6:19:49<2:02:49,  3.87it/s]{'loss': '1.194', 'grad_norm': '1.24', 'learning_rate': '1.273e-05', 'epoch': '74.58'}
+
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+                                                          
+
+ 75%|███████▍  | 83700/112100 [6:20:18<1:56:02,  4.08it/s]{'loss': '1.195', 'grad_norm': '1.218', 'learning_rate': '1.268e-05', 'epoch': '74.67'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 75%|███████▍  | 83800/112100 [6:20:42<1:29:22,  5.28it/s]{'loss': '1.196', 'grad_norm': '1.246', 'learning_rate': '1.264e-05', 'epoch': '74.76'}
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+                                                          
+
+ 75%|███████▍  | 83900/112100 [6:21:10<2:03:19,  3.81it/s]{'loss': '1.195', 'grad_norm': '1.144', 'learning_rate': '1.259e-05', 'epoch': '74.84'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 75%|███████▍  | 84000/112100 [6:21:39<2:01:44,  3.85it/s]{'loss': '1.195', 'grad_norm': '1.34', 'learning_rate': '1.255e-05', 'epoch': '74.93'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 75%|███████▌  | 84100/112100 [6:22:11<2:10:51,  3.57it/s]{'loss': '1.194', 'grad_norm': '1.139', 'learning_rate': '1.25e-05', 'epoch': '75.02'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
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+                                                          
+
+ 75%|███████▌  | 84200/112100 [6:22:40<1:57:30,  3.96it/s]{'loss': '1.195', 'grad_norm': '1.213', 'learning_rate': '1.246e-05', 'epoch': '75.11'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 75%|███████▌  | 84300/112100 [6:23:10<2:10:38,  3.55it/s]{'loss': '1.195', 'grad_norm': '1.113', 'learning_rate': '1.242e-05', 'epoch': '75.2'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                          
+
+ 75%|███████▌  | 84400/112100 [6:23:39<1:56:42,  3.96it/s]{'loss': '1.194', 'grad_norm': '1.575', 'learning_rate': '1.237e-05', 'epoch': '75.29'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+
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+                                                          
+
+ 75%|███████▌  | 84500/112100 [6:24:09<2:09:24,  3.55it/s]{'loss': '1.194', 'grad_norm': '1.157', 'learning_rate': '1.233e-05', 'epoch': '75.38'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
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+                                                          
+
+ 75%|███████▌  | 84600/112100 [6:24:38<2:10:27,  3.51it/s]{'loss': '1.195', 'grad_norm': '1.235', 'learning_rate': '1.228e-05', 'epoch': '75.47'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
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+                                                          
+
+ 76%|███████▌  | 84700/112100 [6:25:09<2:12:01,  3.46it/s]{'loss': '1.193', 'grad_norm': '1.108', 'learning_rate': '1.224e-05', 'epoch': '75.56'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 76%|███████▌  | 84800/112100 [6:25:32<1:49:18,  4.16it/s]{'loss': '1.194', 'grad_norm': '1.683', 'learning_rate': '1.219e-05', 'epoch': '75.65'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
+
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+                                                          
+
+ 76%|███████▌  | 84900/112100 [6:26:01<2:10:48,  3.47it/s]{'loss': '1.194', 'grad_norm': '1.276', 'learning_rate': '1.215e-05', 'epoch': '75.74'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
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+                                                          
+
+ 76%|███████▌  | 85000/112100 [6:26:29<2:11:52,  3.43it/s]{'loss': '1.194', 'grad_norm': '1.482', 'learning_rate': '1.21e-05', 'epoch': '75.83'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.66it/s]
+
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+                                                          
+
+ 76%|███████▌  | 85100/112100 [6:26:59<2:11:24,  3.42it/s]{'loss': '1.196', 'grad_norm': '1.686', 'learning_rate': '1.206e-05', 'epoch': '75.91'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
+ 76%|███████▌  | 85197/112100 [6:27:28<5:53:59,  1.27it/s]
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+                                                          
+
+ 76%|███████▌  | 85200/112100 [6:27:29<3:14:22,  2.31it/s]{'loss': '1.195', 'grad_norm': '1.082', 'learning_rate': '1.201e-05', 'epoch': '76'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.67it/s]
+
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+                                                          
+
+ 76%|███████▌  | 85300/112100 [6:27:59<2:05:33,  3.56it/s]{'loss': '1.194', 'grad_norm': '1.14', 'learning_rate': '1.197e-05', 'epoch': '76.09'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.70it/s]
+
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+                                                          
+
+ 76%|███████▌  | 85400/112100 [6:28:28<1:53:00,  3.94it/s]{'loss': '1.194', 'grad_norm': '1.271', 'learning_rate': '1.193e-05', 'epoch': '76.18'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
+
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+                                                          
+
+ 76%|███████▋  | 85500/112100 [6:28:59<1:56:24,  3.81it/s]{'loss': '1.195', 'grad_norm': '1.192', 'learning_rate': '1.188e-05', 'epoch': '76.27'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
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+                                                          
+
+ 76%|███████▋  | 85600/112100 [6:29:28<1:48:57,  4.05it/s]{'loss': '1.195', 'grad_norm': '1.445', 'learning_rate': '1.184e-05', 'epoch': '76.36'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+
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+                                                          
+
+ 76%|███████▋  | 85700/112100 [6:29:58<1:56:38,  3.77it/s]{'loss': '1.194', 'grad_norm': '1.302', 'learning_rate': '1.179e-05', 'epoch': '76.45'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 77%|███████▋  | 85800/112100 [6:30:22<1:39:53,  4.39it/s]{'loss': '1.194', 'grad_norm': '1.356', 'learning_rate': '1.175e-05', 'epoch': '76.54'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
+
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+                                                          
+
+ 77%|███████▋  | 85900/112100 [6:30:50<2:01:09,  3.60it/s]{'loss': '1.194', 'grad_norm': '1.18', 'learning_rate': '1.17e-05', 'epoch': '76.63'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 77%|███████▋  | 86000/112100 [6:31:19<2:01:12,  3.59it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.195', 'grad_norm': '1.078', 'learning_rate': '1.166e-05', 'epoch': '76.72'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
+
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+                                                          
+
+ 77%|███████▋  | 86100/112100 [6:31:49<2:01:52,  3.56it/s]{'loss': '1.194', 'grad_norm': '1.778', 'learning_rate': '1.161e-05', 'epoch': '76.81'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
+
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+                                                          
+
+ 77%|███████▋  | 86200/112100 [6:32:18<2:06:36,  3.41it/s]{'loss': '1.195', 'grad_norm': '1.342', 'learning_rate': '1.157e-05', 'epoch': '76.9'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+                                                          
+
+ 77%|███████▋  | 86300/112100 [6:32:48<2:03:47,  3.47it/s]{'loss': '1.195', 'grad_norm': '1.149', 'learning_rate': '1.152e-05', 'epoch': '76.99'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 77%|███████▋  | 86400/112100 [6:33:19<2:06:47,  3.38it/s]{'loss': '1.195', 'grad_norm': '1.417', 'learning_rate': '1.148e-05', 'epoch': '77.07'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 77%|███████▋  | 86500/112100 [6:33:49<2:05:05,  3.41it/s]{'loss': '1.194', 'grad_norm': '1.145', 'learning_rate': '1.144e-05', 'epoch': '77.16'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.70it/s]
+
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+                                                          
+
+ 77%|███████▋  | 86600/112100 [6:34:18<2:03:58,  3.43it/s]{'loss': '1.193', 'grad_norm': '1.126', 'learning_rate': '1.139e-05', 'epoch': '77.25'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 77%|███████▋  | 86700/112100 [6:34:48<2:03:04,  3.44it/s]{'loss': '1.193', 'grad_norm': '1.078', 'learning_rate': '1.135e-05', 'epoch': '77.34'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 77%|███████▋  | 86800/112100 [6:35:11<1:42:49,  4.10it/s]{'loss': '1.193', 'grad_norm': '0.9815', 'learning_rate': '1.13e-05', 'epoch': '77.43'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                          
+
+ 78%|███████▊  | 86900/112100 [6:35:39<1:54:37,  3.66it/s]{'loss': '1.194', 'grad_norm': '1.473', 'learning_rate': '1.126e-05', 'epoch': '77.52'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+                                                          
+
+ 78%|███████▊  | 87000/112100 [6:36:08<1:53:51,  3.67it/s]{'loss': '1.194', 'grad_norm': '1.03', 'learning_rate': '1.121e-05', 'epoch': '77.61'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
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+                                                          
+
+ 78%|███████▊  | 87100/112100 [6:36:38<1:45:31,  3.95it/s]{'loss': '1.194', 'grad_norm': '1.673', 'learning_rate': '1.117e-05', 'epoch': '77.7'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.70it/s]
+
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+                                                          
+
+ 78%|███████▊  | 87200/112100 [6:37:07<2:02:33,  3.39it/s]{'loss': '1.194', 'grad_norm': '1.228', 'learning_rate': '1.112e-05', 'epoch': '77.79'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.63it/s]
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+                                                          
+
+ 78%|███████▊  | 87300/112100 [6:37:37<1:47:57,  3.83it/s]{'loss': '1.194', 'grad_norm': '1.134', 'learning_rate': '1.108e-05', 'epoch': '77.88'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.194', 'grad_norm': '1.263', 'learning_rate': '1.103e-05', 'epoch': '77.97'}
+
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.193', 'grad_norm': '1.197', 'learning_rate': '1.099e-05', 'epoch': '78.06'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                          
+
+ 78%|███████▊  | 87600/112100 [6:39:07<1:55:44,  3.53it/s]{'loss': '1.194', 'grad_norm': '1.203', 'learning_rate': '1.094e-05', 'epoch': '78.14'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 78%|███████▊  | 87700/112100 [6:39:37<1:43:44,  3.92it/s]{'loss': '1.193', 'grad_norm': '1.269', 'learning_rate': '1.09e-05', 'epoch': '78.23'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+
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+                                                          
+
+ 78%|███████▊  | 87800/112100 [6:40:02<1:32:51,  4.36it/s]{'loss': '1.194', 'grad_norm': '1.347', 'learning_rate': '1.086e-05', 'epoch': '78.32'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
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+                                                          
+
+ 78%|███████▊  | 87900/112100 [6:40:28<1:50:45,  3.64it/s]{'loss': '1.194', 'grad_norm': '1.268', 'learning_rate': '1.081e-05', 'epoch': '78.41'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+
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+                                                          
+
+ 79%|███████▊  | 88000/112100 [6:40:58<1:51:09,  3.61it/s]{'loss': '1.194', 'grad_norm': '1.718', 'learning_rate': '1.077e-05', 'epoch': '78.5'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+
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+                                                          
+
+ 79%|███████▊  | 88100/112100 [6:41:27<1:49:04,  3.67it/s]{'loss': '1.195', 'grad_norm': '1.096', 'learning_rate': '1.072e-05', 'epoch': '78.59'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+
+ 79%|███████▊  | 88101/112100 [6:41:29<5:36:37,  1.19it/s]
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+                                                          
+
+ 79%|███████▊  | 88200/112100 [6:41:57<1:48:48,  3.66it/s]{'loss': '1.194', 'grad_norm': '1.205', 'learning_rate': '1.068e-05', 'epoch': '78.68'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+                                                          
+
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+                                                          
+
+ 79%|███████▉  | 88400/112100 [6:42:56<1:42:12,  3.86it/s]{'loss': '1.194', 'grad_norm': '1.238', 'learning_rate': '1.059e-05', 'epoch': '78.86'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
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+                                                          
+
+ 79%|███████▉  | 88500/112100 [6:43:25<1:46:51,  3.68it/s]{'loss': '1.195', 'grad_norm': '1.303', 'learning_rate': '1.054e-05', 'epoch': '78.95'}
+
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+
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+                                                          
+
+ 79%|███████▉  | 88600/112100 [6:43:57<1:52:47,  3.47it/s]{'loss': '1.194', 'grad_norm': '1.188', 'learning_rate': '1.05e-05', 'epoch': '79.04'}
+
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+                                                          
+
+ 79%|███████▉  | 88700/112100 [6:44:26<1:53:28,  3.44it/s]{'loss': '1.194', 'grad_norm': '1.321', 'learning_rate': '1.045e-05', 'epoch': '79.13'}
+
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+                                                          
+
+ 79%|███████▉  | 88800/112100 [6:44:51<1:32:53,  4.18it/s]{'loss': '1.193', 'grad_norm': '2.084', 'learning_rate': '1.041e-05', 'epoch': '79.22'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
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+                                                          
+
+ 79%|███████▉  | 88900/112100 [6:45:16<1:51:37,  3.46it/s]{'loss': '1.193', 'grad_norm': '1.177', 'learning_rate': '1.037e-05', 'epoch': '79.3'}
+
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+                                                          
+
+ 79%|███████▉  | 89000/112100 [6:45:47<1:51:33,  3.45it/s]{'loss': '1.194', 'grad_norm': '1.047', 'learning_rate': '1.032e-05', 'epoch': '79.39'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
+
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+                                                          
+
+ 79%|███████▉  | 89100/112100 [6:46:15<1:52:47,  3.40it/s]{'loss': '1.193', 'grad_norm': '0.9923', 'learning_rate': '1.028e-05', 'epoch': '79.48'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 80%|███████▉  | 89200/112100 [6:46:45<1:47:22,  3.55it/s]{'loss': '1.193', 'grad_norm': '1.278', 'learning_rate': '1.023e-05', 'epoch': '79.57'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+
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+                                                          
+
+ 80%|███████▉  | 89300/112100 [6:47:14<1:50:05,  3.45it/s]{'loss': '1.195', 'grad_norm': '1.104', 'learning_rate': '1.019e-05', 'epoch': '79.66'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 80%|███████▉  | 89400/112100 [6:47:44<1:35:18,  3.97it/s]{'loss': '1.193', 'grad_norm': '1.404', 'learning_rate': '1.014e-05', 'epoch': '79.75'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
+
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+                                                          
+
+ 80%|███████▉  | 89500/112100 [6:48:13<1:45:23,  3.57it/s]{'loss': '1.193', 'grad_norm': '1.296', 'learning_rate': '1.01e-05', 'epoch': '79.84'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 80%|███████▉  | 89600/112100 [6:48:43<1:34:15,  3.98it/s]{'loss': '1.194', 'grad_norm': '1.241', 'learning_rate': '1.005e-05', 'epoch': '79.93'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.66it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.66it/s]
+
+ 80%|███████▉  | 89601/112100 [6:48:45<5:02:33,  1.24it/s]
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+                                                          
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.194', 'grad_norm': '1.084', 'learning_rate': '9.964e-06', 'epoch': '80.11'}
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+                                                          
+
+ 80%|████████  | 89900/112100 [6:50:06<1:39:00,  3.74it/s]{'loss': '1.193', 'grad_norm': '1.386', 'learning_rate': '9.919e-06', 'epoch': '80.2'}
+
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+                                                          
+
+ 80%|████████  | 90000/112100 [6:50:35<1:31:49,  4.01it/s]{'loss': '1.193', 'grad_norm': '1.391', 'learning_rate': '9.875e-06', 'epoch': '80.29'}
+
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+                                                          
+
+ 80%|████████  | 90100/112100 [6:51:06<1:46:28,  3.44it/s]{'loss': '1.193', 'grad_norm': '1.064', 'learning_rate': '9.83e-06', 'epoch': '80.37'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 80%|████████  | 90200/112100 [6:51:35<1:33:52,  3.89it/s]{'loss': '1.193', 'grad_norm': '1.412', 'learning_rate': '9.785e-06', 'epoch': '80.46'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+                                                          
+
+ 81%|████████  | 90300/112100 [6:52:05<1:47:02,  3.39it/s]{'loss': '1.194', 'grad_norm': '1.1', 'learning_rate': '9.741e-06', 'epoch': '80.55'}
+
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+                                                          
+
+ 81%|████████  | 90400/112100 [6:52:33<1:33:46,  3.86it/s]{'loss': '1.193', 'grad_norm': '1.156', 'learning_rate': '9.696e-06', 'epoch': '80.64'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
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+                                                          
+
+ 81%|████████  | 90500/112100 [6:53:03<1:44:25,  3.45it/s]{'loss': '1.194', 'grad_norm': '1.028', 'learning_rate': '9.652e-06', 'epoch': '80.73'}
+
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+                                                          
+
+ 81%|████████  | 90600/112100 [6:53:32<1:43:26,  3.46it/s]{'loss': '1.194', 'grad_norm': '1.047', 'learning_rate': '9.607e-06', 'epoch': '80.82'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
+
+ 81%|████████  | 90700/112100 [6:54:02<1:44:09,  3.42it/s]{'loss': '1.193', 'grad_norm': '1.071', 'learning_rate': '9.563e-06', 'epoch': '80.91'}
+
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+                                                          
+
+ 81%|████████  | 90800/112100 [6:54:27<1:14:23,  4.77it/s]{'loss': '1.193', 'grad_norm': '1.213', 'learning_rate': '9.518e-06', 'epoch': '81'}
+
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+                                                          
+
+ 81%|████████  | 90900/112100 [6:54:55<1:43:09,  3.43it/s]{'loss': '1.193', 'grad_norm': '2.05', 'learning_rate': '9.474e-06', 'epoch': '81.09'}
+
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+                                                          
+
+ 81%|████████  | 91000/112100 [6:55:24<1:42:26,  3.43it/s]{'loss': '1.194', 'grad_norm': '1.317', 'learning_rate': '9.429e-06', 'epoch': '81.18'}
+
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+                                                          
+
+ 81%|████████▏ | 91100/112100 [6:55:54<1:41:28,  3.45it/s]{'loss': '1.194', 'grad_norm': '0.9772', 'learning_rate': '9.384e-06', 'epoch': '81.27'}
+
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+                                                          
+
+ 81%|████████▏ | 91200/112100 [6:56:22<1:37:56,  3.56it/s]{'loss': '1.192', 'grad_norm': '1.026', 'learning_rate': '9.34e-06', 'epoch': '81.36'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 81%|████████▏ | 91300/112100 [6:56:53<1:39:37,  3.48it/s]{'loss': '1.194', 'grad_norm': '1.315', 'learning_rate': '9.295e-06', 'epoch': '81.45'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.62it/s]
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+                                                          
+
+ 82%|████████▏ | 91400/112100 [6:57:22<1:35:31,  3.61it/s]{'loss': '1.194', 'grad_norm': '1.11', 'learning_rate': '9.251e-06', 'epoch': '81.53'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+
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+ 82%|████████▏ | 91500/112100 [6:57:51<1:35:29,  3.60it/s]
+                                                          
+
+ 82%|████████▏ | 91500/112100 [6:57:51<1:35:29,  3.60it/s]{'loss': '1.194', 'grad_norm': '1.215', 'learning_rate': '9.206e-06', 'epoch': '81.62'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
+
+ 82%|████████▏ | 91501/112100 [6:57:53<4:53:32,  1.17it/s]
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+ 82%|████████▏ | 91600/112100 [6:58:20<1:29:39,  3.81it/s]
+                                                          
+
+ 82%|████████▏ | 91600/112100 [6:58:20<1:29:39,  3.81it/s]{'loss': '1.193', 'grad_norm': '0.9832', 'learning_rate': '9.161e-06', 'epoch': '81.71'}
+
+
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.193', 'grad_norm': '1.041', 'learning_rate': '9.117e-06', 'epoch': '81.8'}
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+                                                          
+
+ 82%|████████▏ | 91800/112100 [6:59:15<1:09:41,  4.85it/s]{'loss': '1.194', 'grad_norm': '1.365', 'learning_rate': '9.072e-06', 'epoch': '81.89'}
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+                                                          
+
+ 82%|████████▏ | 91900/112100 [6:59:41<1:31:36,  3.68it/s]{'loss': '1.193', 'grad_norm': '1.262', 'learning_rate': '9.028e-06', 'epoch': '81.98'}
+
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+                                                          
+
+ 82%|████████▏ | 92000/112100 [7:00:11<1:37:18,  3.44it/s]{'loss': '1.194', 'grad_norm': '1.382', 'learning_rate': '8.983e-06', 'epoch': '82.07'}
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+                                                          
+
+ 82%|████████▏ | 92100/112100 [7:00:41<1:35:15,  3.50it/s]{'loss': '1.193', 'grad_norm': '1.154', 'learning_rate': '8.938e-06', 'epoch': '82.16'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.194', 'grad_norm': '1.121', 'learning_rate': '8.894e-06', 'epoch': '82.25'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                          
+
+ 82%|████████▏ | 92300/112100 [7:01:40<1:37:13,  3.39it/s]{'loss': '1.194', 'grad_norm': '1.271', 'learning_rate': '8.849e-06', 'epoch': '82.34'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                          
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.193', 'grad_norm': '1.333', 'learning_rate': '8.805e-06', 'epoch': '82.43'}
+
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+                                                          
+
+ 83%|████████▎ | 92500/112100 [7:02:39<1:33:26,  3.50it/s]{'loss': '1.194', 'grad_norm': '1.546', 'learning_rate': '8.76e-06', 'epoch': '82.52'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 83%|████████▎ | 92600/112100 [7:03:08<1:32:30,  3.51it/s]{'loss': '1.194', 'grad_norm': '1.074', 'learning_rate': '8.716e-06', 'epoch': '82.61'}
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.193', 'grad_norm': '2.184', 'learning_rate': '8.671e-06', 'epoch': '82.69'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.59it/s]
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+                                                          
+
+ 83%|████████▎ | 92800/112100 [7:04:04<1:10:14,  4.58it/s]{'loss': '1.193', 'grad_norm': '1.49', 'learning_rate': '8.627e-06', 'epoch': '82.78'}
+
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+                                                          
+
+ 83%|████████▎ | 92900/112100 [7:04:30<1:14:23,  4.30it/s]{'loss': '1.192', 'grad_norm': '1.183', 'learning_rate': '8.582e-06', 'epoch': '82.87'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.61it/s]
+
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+                                                          
+
+ 83%|████████▎ | 93000/112100 [7:04:59<1:27:47,  3.63it/s]{'loss': '1.194', 'grad_norm': '1.104', 'learning_rate': '8.537e-06', 'epoch': '82.96'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 83%|████████▎ | 93100/112100 [7:05:31<1:17:35,  4.08it/s]{'loss': '1.193', 'grad_norm': '1.161', 'learning_rate': '8.493e-06', 'epoch': '83.05'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
+
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+                                                          
+
+ 83%|████████▎ | 93200/112100 [7:06:00<1:29:37,  3.51it/s]{'loss': '1.193', 'grad_norm': '1.403', 'learning_rate': '8.449e-06', 'epoch': '83.14'}
+
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+                                                          
+
+ 83%|████████▎ | 93300/112100 [7:06:30<1:21:10,  3.86it/s]{'loss': '1.193', 'grad_norm': '1.135', 'learning_rate': '8.404e-06', 'epoch': '83.23'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.75it/s]
+
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.193', 'grad_norm': '0.9354', 'learning_rate': '8.36e-06', 'epoch': '83.32'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.67it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.66it/s]
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+                                                          
+
+ 83%|████████▎ | 93500/112100 [7:07:29<1:21:22,  3.81it/s]{'loss': '1.194', 'grad_norm': '1.39', 'learning_rate': '8.315e-06', 'epoch': '83.41'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+
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+                                                          
+
+ 83%|████████▎ | 93600/112100 [7:07:59<1:29:58,  3.43it/s]{'loss': '1.193', 'grad_norm': '1.092', 'learning_rate': '8.27e-06', 'epoch': '83.5'}
+
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+                                                          
+
+ 84%|████████▎ | 93700/112100 [7:08:28<1:22:30,  3.72it/s]{'loss': '1.193', 'grad_norm': '1.613', 'learning_rate': '8.226e-06', 'epoch': '83.59'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.76it/s]
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+                                                          
+
+ 84%|████████▎ | 93800/112100 [7:08:55<1:16:57,  3.96it/s]{'loss': '1.193', 'grad_norm': '1.131', 'learning_rate': '8.181e-06', 'epoch': '83.68'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                          
+
+ 84%|████████▍ | 93900/112100 [7:09:18<1:04:31,  4.70it/s]{'loss': '1.192', 'grad_norm': '1.352', 'learning_rate': '8.136e-06', 'epoch': '83.76'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
+
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+                                                          
+
+ 84%|████████▍ | 94000/112100 [7:09:48<1:27:24,  3.45it/s]{'loss': '1.193', 'grad_norm': '1.349', 'learning_rate': '8.092e-06', 'epoch': '83.85'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
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+                                                          
+
+ 84%|████████▍ | 94100/112100 [7:10:17<1:17:52,  3.85it/s]{'loss': '1.194', 'grad_norm': '1.348', 'learning_rate': '8.047e-06', 'epoch': '83.94'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
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+                                                          
+
+ 84%|████████▍ | 94200/112100 [7:10:49<1:24:23,  3.54it/s]{'loss': '1.193', 'grad_norm': '0.9787', 'learning_rate': '8.003e-06', 'epoch': '84.03'}
+
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+                                                          
+
+ 84%|████████▍ | 94300/112100 [7:11:18<1:21:33,  3.64it/s]{'loss': '1.193', 'grad_norm': '1.046', 'learning_rate': '7.958e-06', 'epoch': '84.12'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                          
+
+ 84%|████████▍ | 94400/112100 [7:11:49<1:22:15,  3.59it/s]{'loss': '1.192', 'grad_norm': '1.271', 'learning_rate': '7.913e-06', 'epoch': '84.21'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
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+                                                          
+
+ 84%|████████▍ | 94500/112100 [7:12:17<1:25:32,  3.43it/s]{'loss': '1.194', 'grad_norm': '1.157', 'learning_rate': '7.869e-06', 'epoch': '84.3'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+                                                          
+
+ 84%|████████▍ | 94600/112100 [7:12:48<1:28:02,  3.31it/s]{'loss': '1.193', 'grad_norm': '1.621', 'learning_rate': '7.824e-06', 'epoch': '84.39'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.193', 'grad_norm': '1.051', 'learning_rate': '7.78e-06', 'epoch': '84.48'}
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+                                                          
+
+ 85%|████████▍ | 94800/112100 [7:13:45<1:10:19,  4.10it/s]{'loss': '1.193', 'grad_norm': '1.402', 'learning_rate': '7.735e-06', 'epoch': '84.57'}
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+                                                          
+
+ 85%|████████▍ | 94900/112100 [7:14:08<1:09:16,  4.14it/s]{'loss': '1.193', 'grad_norm': '1.157', 'learning_rate': '7.69e-06', 'epoch': '84.66'}
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+                                                          
+
+ 85%|████████▍ | 95000/112100 [7:14:37<1:18:37,  3.62it/s]{'loss': '1.193', 'grad_norm': '1.319', 'learning_rate': '7.646e-06', 'epoch': '84.75'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                          
+
+ 85%|████████▍ | 95100/112100 [7:15:06<1:22:40,  3.43it/s]{'loss': '1.192', 'grad_norm': '1.452', 'learning_rate': '7.601e-06', 'epoch': '84.84'}
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+                                                          
+
+ 85%|████████▍ | 95200/112100 [7:15:36<1:21:23,  3.46it/s]{'loss': '1.192', 'grad_norm': '1.137', 'learning_rate': '7.557e-06', 'epoch': '84.92'}
+
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+                                                          
+
+ 85%|████████▌ | 95300/112100 [7:16:07<1:21:15,  3.45it/s]{'loss': '1.194', 'grad_norm': '1.315', 'learning_rate': '7.512e-06', 'epoch': '85.01'}
+
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+                                                          
+
+ 85%|████████▌ | 95400/112100 [7:16:37<1:09:23,  4.01it/s]{'loss': '1.193', 'grad_norm': '1.476', 'learning_rate': '7.467e-06', 'epoch': '85.1'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
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+                                                          
+
+ 85%|████████▌ | 95500/112100 [7:17:06<1:17:40,  3.56it/s]{'loss': '1.192', 'grad_norm': '0.9793', 'learning_rate': '7.423e-06', 'epoch': '85.19'}
+
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+                                                          
+
+ 85%|████████▌ | 95600/112100 [7:17:36<1:10:53,  3.88it/s]{'loss': '1.193', 'grad_norm': '1.543', 'learning_rate': '7.378e-06', 'epoch': '85.28'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 85%|████████▌ | 95700/112100 [7:18:06<1:18:34,  3.48it/s]{'loss': '1.192', 'grad_norm': '1.463', 'learning_rate': '7.334e-06', 'epoch': '85.37'}
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+                                                        
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.193', 'grad_norm': '1.236', 'learning_rate': '7.289e-06', 'epoch': '85.46'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.66it/s]
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+                                                        
+
+ 86%|████████▌ | 95900/112100 [7:18:59<59:14,  4.56it/s]{'loss': '1.194', 'grad_norm': '2.068', 'learning_rate': '7.244e-06', 'epoch': '85.55'}
+
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+                                                          
+
+ 86%|████████▌ | 96000/112100 [7:19:27<1:02:49,  4.27it/s]{'loss': '1.193', 'grad_norm': '1.252', 'learning_rate': '7.2e-06', 'epoch': '85.64'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.63it/s]
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+                                                          
+
+ 86%|████████▌ | 96100/112100 [7:19:57<1:16:13,  3.50it/s]{'loss': '1.193', 'grad_norm': '1.253', 'learning_rate': '7.155e-06', 'epoch': '85.73'}
+
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+                                                          
+
+ 86%|████████▌ | 96200/112100 [7:20:26<1:08:38,  3.86it/s]{'loss': '1.192', 'grad_norm': '1.18', 'learning_rate': '7.111e-06', 'epoch': '85.82'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                          
+
+ 86%|████████▌ | 96300/112100 [7:20:56<1:15:26,  3.49it/s]{'loss': '1.194', 'grad_norm': '1.391', 'learning_rate': '7.066e-06', 'epoch': '85.91'}
+
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+                                                          
+
+ 86%|████████▌ | 96400/112100 [7:21:25<1:04:31,  4.06it/s]{'loss': '1.193', 'grad_norm': '1.231', 'learning_rate': '7.021e-06', 'epoch': '86'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.63it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
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+                                                          
+
+ 86%|████████▌ | 96500/112100 [7:21:57<1:14:51,  3.47it/s]{'loss': '1.193', 'grad_norm': '1.074', 'learning_rate': '6.977e-06', 'epoch': '86.08'}
+
+
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+                                                          
+
+ 86%|████████▌ | 96600/112100 [7:22:26<1:07:53,  3.81it/s]{'loss': '1.192', 'grad_norm': '1.124', 'learning_rate': '6.932e-06', 'epoch': '86.17'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
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+                                                          
+
+ 86%|████████▋ | 96700/112100 [7:22:56<1:14:59,  3.42it/s]{'loss': '1.193', 'grad_norm': '1.379', 'learning_rate': '6.888e-06', 'epoch': '86.26'}
+
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+                                                        
+
+ 86%|████████▋ | 96800/112100 [7:23:24<50:57,  5.00it/s]{'loss': '1.193', 'grad_norm': '0.8468', 'learning_rate': '6.843e-06', 'epoch': '86.35'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                        
+
+ 86%|████████▋ | 96900/112100 [7:23:50<59:09,  4.28it/s]{'loss': '1.192', 'grad_norm': '1.474', 'learning_rate': '6.798e-06', 'epoch': '86.44'}
+
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+                                                          
+
+ 87%|████████▋ | 97000/112100 [7:24:19<1:12:12,  3.48it/s]{'loss': '1.193', 'grad_norm': '1.415', 'learning_rate': '6.754e-06', 'epoch': '86.53'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.42it/s]
+
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+                                                          
+
+ 87%|████████▋ | 97100/112100 [7:24:49<1:11:03,  3.52it/s]{'loss': '1.193', 'grad_norm': '1.393', 'learning_rate': '6.71e-06', 'epoch': '86.62'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
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+                                                          
+
+ 87%|████████▋ | 97200/112100 [7:25:18<1:08:34,  3.62it/s]{'loss': '1.193', 'grad_norm': '1.76', 'learning_rate': '6.665e-06', 'epoch': '86.71'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
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+                                                          
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.133', 'learning_rate': '6.62e-06', 'epoch': '86.8'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                          
+
+ 87%|████████▋ | 97400/112100 [7:26:18<1:07:40,  3.62it/s]{'loss': '1.193', 'grad_norm': '1.085', 'learning_rate': '6.576e-06', 'epoch': '86.89'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                        
+
+ 87%|████████▋ | 97500/112100 [7:26:48<58:52,  4.13it/s]{'loss': '1.193', 'grad_norm': '0.9107', 'learning_rate': '6.531e-06', 'epoch': '86.98'}
+
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+
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+                                                          
+
+ 87%|████████▋ | 97600/112100 [7:27:20<1:04:56,  3.72it/s]{'loss': '1.192', 'grad_norm': '1.284', 'learning_rate': '6.487e-06', 'epoch': '87.07'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
+
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+                                                        
+
+ 87%|████████▋ | 97700/112100 [7:27:50<56:43,  4.23it/s]{'loss': '1.193', 'grad_norm': '1.671', 'learning_rate': '6.442e-06', 'epoch': '87.15'}
+
+
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+                                                        
+
+ 87%|████████▋ | 97800/112100 [7:28:15<52:29,  4.54it/s]{'loss': '1.193', 'grad_norm': '1.151', 'learning_rate': '6.397e-06', 'epoch': '87.24'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
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+                                                        
+
+ 87%|████████▋ | 97900/112100 [7:28:41<54:36,  4.33it/s]{'loss': '1.192', 'grad_norm': '1.078', 'learning_rate': '6.353e-06', 'epoch': '87.33'}
+
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+                                                          
+
+ 87%|████████▋ | 98000/112100 [7:29:10<1:08:28,  3.43it/s]{'loss': '1.193', 'grad_norm': '1.14', 'learning_rate': '6.308e-06', 'epoch': '87.42'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.50it/s]
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+                                                          
+
+ 88%|████████▊ | 98100/112100 [7:29:40<1:07:34,  3.45it/s]{'loss': '1.193', 'grad_norm': '1.519', 'learning_rate': '6.264e-06', 'epoch': '87.51'}
+
+
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+                                                          
+
+ 88%|████████▊ | 98200/112100 [7:30:09<1:07:36,  3.43it/s]{'loss': '1.193', 'grad_norm': '1.857', 'learning_rate': '6.219e-06', 'epoch': '87.6'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
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+                                                          
+
+ 88%|████████▊ | 98300/112100 [7:30:39<1:05:24,  3.52it/s]{'loss': '1.192', 'grad_norm': '2.084', 'learning_rate': '6.174e-06', 'epoch': '87.69'}
+
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+                                                          
+
+ 88%|████████▊ | 98400/112100 [7:31:08<1:06:38,  3.43it/s]{'loss': '1.193', 'grad_norm': '1.239', 'learning_rate': '6.13e-06', 'epoch': '87.78'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                          
+
+ 88%|████████▊ | 98500/112100 [7:31:39<1:00:18,  3.76it/s]{'loss': '1.192', 'grad_norm': '1.451', 'learning_rate': '6.085e-06', 'epoch': '87.87'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
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+                                                          
+
+ 88%|████████▊ | 98600/112100 [7:32:08<1:04:30,  3.49it/s]{'loss': '1.192', 'grad_norm': '1.393', 'learning_rate': '6.041e-06', 'epoch': '87.96'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+
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+                                                          
+
+ 88%|████████▊ | 98700/112100 [7:32:40<1:00:52,  3.67it/s]{'loss': '1.193', 'grad_norm': '1.342', 'learning_rate': '5.996e-06', 'epoch': '88.05'}
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+                                                        
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.107', 'learning_rate': '5.951e-06', 'epoch': '88.14'}
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+                                                        
+
+ 88%|████████▊ | 98900/112100 [7:33:31<43:14,  5.09it/s]{'loss': '1.193', 'grad_norm': '1.144', 'learning_rate': '5.907e-06', 'epoch': '88.22'}
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+                                                          
+
+ 88%|████████▊ | 99000/112100 [7:34:01<1:02:07,  3.51it/s]{'loss': '1.194', 'grad_norm': '1.396', 'learning_rate': '5.862e-06', 'epoch': '88.31'}
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+                                                        
+
+ 88%|████████▊ | 99100/112100 [7:34:30<49:10,  4.41it/s]{'loss': '1.192', 'grad_norm': '1.361', 'learning_rate': '5.818e-06', 'epoch': '88.4'}
+
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+                                                        
+
+ 88%|████████▊ | 99200/112100 [7:35:00<57:59,  3.71it/s]{'loss': '1.193', 'grad_norm': '1.219', 'learning_rate': '5.773e-06', 'epoch': '88.49'}
+
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+                                                        
+
+ 89%|████████▊ | 99300/112100 [7:35:29<50:15,  4.25it/s]{'loss': '1.192', 'grad_norm': '1.162', 'learning_rate': '5.729e-06', 'epoch': '88.58'}
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+                                                          
+
+ 89%|████████▊ | 99400/112100 [7:36:00<1:02:07,  3.41it/s]{'loss': '1.193', 'grad_norm': '1.329', 'learning_rate': '5.684e-06', 'epoch': '88.67'}
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+                                                        
+
+ 89%|████████▉ | 99500/112100 [7:36:28<59:01,  3.56it/s]{'loss': '1.193', 'grad_norm': '1.214', 'learning_rate': '5.64e-06', 'epoch': '88.76'}
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+                                                          
+
+ 89%|████████▉ | 99600/112100 [7:36:59<1:00:22,  3.45it/s]{'loss': '1.193', 'grad_norm': '1.309', 'learning_rate': '5.595e-06', 'epoch': '88.85'}
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+                                                        
+
+ 89%|████████▉ | 99700/112100 [7:37:28<57:46,  3.58it/s]{'loss': '1.193', 'grad_norm': '0.9985', 'learning_rate': '5.55e-06', 'epoch': '88.94'}
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+                                                        
+
+ 89%|████████▉ | 99800/112100 [7:37:58<50:26,  4.06it/s]{'loss': '1.192', 'grad_norm': '1.244', 'learning_rate': '5.506e-06', 'epoch': '89.03'}
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+                                                        
+
+ 89%|████████▉ | 99900/112100 [7:38:22<47:27,  4.29it/s]{'loss': '1.192', 'grad_norm': '1.177', 'learning_rate': '5.461e-06', 'epoch': '89.12'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                         
+
+ 89%|████████▉ | 100000/112100 [7:38:52<56:00,  3.60it/s]{'loss': '1.192', 'grad_norm': '1.643', 'learning_rate': '5.417e-06', 'epoch': '89.21'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.69it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.69it/s]
+
+ 89%|████████▉ | 100001/112100 [7:38:54<2:47:32,  1.20it/s]
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+                                                         
+
+ 89%|████████▉ | 100100/112100 [7:39:22<56:58,  3.51it/s]{'loss': '1.191', 'grad_norm': '1.1', 'learning_rate': '5.372e-06', 'epoch': '89.3'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
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+                                                         
+
+ 89%|████████▉ | 100200/112100 [7:39:52<52:55,  3.75it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.143', 'learning_rate': '5.327e-06', 'epoch': '89.38'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
+
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+                                                         
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.294', 'learning_rate': '5.283e-06', 'epoch': '89.47'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.68it/s]
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+                                                         
+
+ 90%|████████▉ | 100400/112100 [7:40:51<48:26,  4.03it/s]{'loss': '1.193', 'grad_norm': '1.057', 'learning_rate': '5.238e-06', 'epoch': '89.56'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.64it/s]
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+                                                         
+
+ 90%|████████▉ | 100500/112100 [7:41:21<52:00,  3.72it/s]{'loss': '1.193', 'grad_norm': '1.09', 'learning_rate': '5.194e-06', 'epoch': '89.65'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 90%|████████▉ | 100600/112100 [7:41:51<47:20,  4.05it/s]{'loss': '1.192', 'grad_norm': '3.025', 'learning_rate': '5.149e-06', 'epoch': '89.74'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.33it/s]
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+                                                         
+
+ 90%|████████▉ | 100700/112100 [7:42:22<55:26,  3.43it/s]{'loss': '1.193', 'grad_norm': '1.404', 'learning_rate': '5.104e-06', 'epoch': '89.83'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 90%|████████▉ | 100800/112100 [7:42:48<40:14,  4.68it/s]{'loss': '1.192', 'grad_norm': '1.395', 'learning_rate': '5.06e-06', 'epoch': '89.92'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
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+
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+                                                           
+
+ 90%|█████████ | 100900/112100 [7:43:15<1:02:04,  3.01it/s]{'loss': '1.193', 'grad_norm': '1.14', 'learning_rate': '5.015e-06', 'epoch': '90.01'}
+
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+                                                         
+
+ 90%|█████████ | 101000/112100 [7:43:44<47:11,  3.92it/s]{'loss': '1.191', 'grad_norm': '1.039', 'learning_rate': '4.971e-06', 'epoch': '90.1'}
+
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.22it/s]
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+                                                         
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.083', 'learning_rate': '4.926e-06', 'epoch': '90.19'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.43it/s]
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+                                                         
+
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+                                                         
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '0.9723', 'learning_rate': '4.837e-06', 'epoch': '90.37'}
+
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+                                                         
+
+ 90%|█████████ | 101400/112100 [7:45:44<51:38,  3.45it/s]{'loss': '1.192', 'grad_norm': '1.222', 'learning_rate': '4.793e-06', 'epoch': '90.46'}
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+                                                         
+
+ 91%|█████████ | 101500/112100 [7:46:14<51:52,  3.41it/s]{'loss': '1.192', 'grad_norm': '1.322', 'learning_rate': '4.748e-06', 'epoch': '90.54'}
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+                                                         
+
+ 91%|█████████ | 101600/112100 [7:46:43<52:59,  3.30it/s]{'loss': '1.192', 'grad_norm': '1.315', 'learning_rate': '4.703e-06', 'epoch': '90.63'}
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+                                                         
+
+ 91%|█████████ | 101700/112100 [7:47:14<48:50,  3.55it/s]{'loss': '1.193', 'grad_norm': '1.033', 'learning_rate': '4.659e-06', 'epoch': '90.72'}
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+                                                         
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.392', 'learning_rate': '4.614e-06', 'epoch': '90.81'}
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+                                                         
+
+ 91%|█████████ | 101900/112100 [7:48:05<47:38,  3.57it/s]{'loss': '1.192', 'grad_norm': '1.065', 'learning_rate': '4.57e-06', 'epoch': '90.9'}
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+                                                         
+
+ 91%|█████████ | 102000/112100 [7:48:35<48:52,  3.44it/s]{'loss': '1.193', 'grad_norm': '1.805', 'learning_rate': '4.525e-06', 'epoch': '90.99'}
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+                                                         
+
+ 91%|█████████ | 102100/112100 [7:49:08<48:50,  3.41it/s]{'loss': '1.193', 'grad_norm': '1.242', 'learning_rate': '4.48e-06', 'epoch': '91.08'}
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+                                                         
+
+ 91%|█████████ | 102200/112100 [7:49:37<47:05,  3.50it/s]{'loss': '1.193', 'grad_norm': '0.9102', 'learning_rate': '4.436e-06', 'epoch': '91.17'}
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+                                                         
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.326', 'learning_rate': '4.391e-06', 'epoch': '91.26'}
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+                                                         
+
+ 91%|█████████▏| 102400/112100 [7:50:37<47:27,  3.41it/s]{'loss': '1.192', 'grad_norm': '1.334', 'learning_rate': '4.347e-06', 'epoch': '91.35'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 91%|█████████▏| 102500/112100 [7:51:08<45:23,  3.52it/s]{'loss': '1.192', 'grad_norm': '1.174', 'learning_rate': '4.302e-06', 'epoch': '91.44'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 92%|█████████▏| 102600/112100 [7:51:37<46:35,  3.40it/s]{'loss': '1.192', 'grad_norm': '1.297', 'learning_rate': '4.257e-06', 'epoch': '91.53'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 92%|█████████▏| 102700/112100 [7:52:08<42:29,  3.69it/s]{'loss': '1.192', 'grad_norm': '1.483', 'learning_rate': '4.213e-06', 'epoch': '91.61'}
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+                                                         
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.193', 'grad_norm': '1.372', 'learning_rate': '4.168e-06', 'epoch': '91.7'}
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+                                                         
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+                                                         
+
+ 92%|█████████▏| 103000/112100 [7:53:29<43:46,  3.46it/s]{'loss': '1.192', 'grad_norm': '1.387', 'learning_rate': '4.079e-06', 'epoch': '91.88'}
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+                                                         
+
+ 92%|█████████▏| 103100/112100 [7:54:00<37:08,  4.04it/s]{'loss': '1.192', 'grad_norm': '1.214', 'learning_rate': '4.035e-06', 'epoch': '91.97'}
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+                                                         
+
+ 92%|█████████▏| 103200/112100 [7:54:32<39:34,  3.75it/s]{'loss': '1.192', 'grad_norm': '1.043', 'learning_rate': '3.99e-06', 'epoch': '92.06'}
+
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+                                                         
+
+ 92%|█████████▏| 103300/112100 [7:55:02<33:24,  4.39it/s]{'loss': '1.192', 'grad_norm': '1.121', 'learning_rate': '3.946e-06', 'epoch': '92.15'}
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+                                                         
+
+ 92%|█████████▏| 103400/112100 [7:55:32<38:36,  3.76it/s]{'loss': '1.192', 'grad_norm': '1.153', 'learning_rate': '3.901e-06', 'epoch': '92.24'}
+
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+                                                         
+
+ 92%|█████████▏| 103500/112100 [7:56:01<35:48,  4.00it/s]{'loss': '1.191', 'grad_norm': '1.322', 'learning_rate': '3.856e-06', 'epoch': '92.33'}
+
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+                                                         
+
+ 92%|█████████▏| 103600/112100 [7:56:32<39:48,  3.56it/s]{'loss': '1.193', 'grad_norm': '1.385', 'learning_rate': '3.812e-06', 'epoch': '92.42'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.274', 'learning_rate': '3.767e-06', 'epoch': '92.51'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.41it/s]
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+                                                         
+
+ 93%|█████████▎| 103800/112100 [7:57:24<32:34,  4.25it/s]{'loss': '1.192', 'grad_norm': '1.067', 'learning_rate': '3.723e-06', 'epoch': '92.6'}
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 93%|█████████▎| 103900/112100 [7:57:53<34:56,  3.91it/s]{'loss': '1.193', 'grad_norm': '1.233', 'learning_rate': '3.678e-06', 'epoch': '92.69'}
+
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+                                                         
+
+ 93%|█████████▎| 104000/112100 [7:58:22<36:27,  3.70it/s]{'loss': '1.192', 'grad_norm': '1.218', 'learning_rate': '3.633e-06', 'epoch': '92.77'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.36it/s]
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+                                                         
+
+ 93%|█████████▎| 104100/112100 [7:58:51<37:45,  3.53it/s]{'loss': '1.192', 'grad_norm': '0.9975', 'learning_rate': '3.589e-06', 'epoch': '92.86'}
+
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+                                                         
+
+ 93%|█████████▎| 104200/112100 [7:59:20<36:51,  3.57it/s]{'loss': '1.192', 'grad_norm': '1.313', 'learning_rate': '3.544e-06', 'epoch': '92.95'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
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+{'loss': '1.192', 'grad_norm': '1.141', 'learning_rate': '3.5e-06', 'epoch': '93.04'}
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 93%|█████████▎| 104400/112100 [8:00:21<37:00,  3.47it/s]{'loss': '1.192', 'grad_norm': '1.516', 'learning_rate': '3.455e-06', 'epoch': '93.13'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
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+                                                         
+
+ 93%|█████████▎| 104500/112100 [8:00:52<36:33,  3.46it/s]{'loss': '1.191', 'grad_norm': '1.046', 'learning_rate': '3.411e-06', 'epoch': '93.22'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 93%|█████████▎| 104600/112100 [8:01:21<37:12,  3.36it/s]{'loss': '1.191', 'grad_norm': '1.149', 'learning_rate': '3.366e-06', 'epoch': '93.31'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.45it/s]
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+                                                         
+
+ 93%|█████████▎| 104700/112100 [8:01:50<27:34,  4.47it/s]{'loss': '1.192', 'grad_norm': '1.686', 'learning_rate': '3.322e-06', 'epoch': '93.4'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 93%|█████████▎| 104800/112100 [8:02:14<32:41,  3.72it/s]{'loss': '1.191', 'grad_norm': '1.345', 'learning_rate': '3.277e-06', 'epoch': '93.49'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 94%|█████████▎| 104900/112100 [8:02:45<33:52,  3.54it/s]{'loss': '1.192', 'grad_norm': '0.982', 'learning_rate': '3.232e-06', 'epoch': '93.58'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 94%|█████████▎| 105000/112100 [8:03:14<33:04,  3.58it/s]{'loss': '1.192', 'grad_norm': '1.276', 'learning_rate': '3.188e-06', 'epoch': '93.67'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 94%|█████████▍| 105100/112100 [8:03:44<32:02,  3.64it/s]{'loss': '1.193', 'grad_norm': '0.9474', 'learning_rate': '3.143e-06', 'epoch': '93.76'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 94%|█████████▍| 105200/112100 [8:04:14<32:51,  3.50it/s]{'loss': '1.193', 'grad_norm': '1.235', 'learning_rate': '3.099e-06', 'epoch': '93.85'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
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+                                                         
+
+ 94%|█████████▍| 105300/112100 [8:04:44<30:04,  3.77it/s]{'loss': '1.192', 'grad_norm': '1.147', 'learning_rate': '3.054e-06', 'epoch': '93.93'}
+
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+                                                         
+
+ 94%|█████████▍| 105400/112100 [8:05:15<33:03,  3.38it/s]{'loss': '1.192', 'grad_norm': '1.379', 'learning_rate': '3.009e-06', 'epoch': '94.02'}
+
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+                                                         
+
+ 94%|█████████▍| 105500/112100 [8:05:45<29:50,  3.69it/s]{'loss': '1.192', 'grad_norm': '1.578', 'learning_rate': '2.965e-06', 'epoch': '94.11'}
+
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+                                                         
+
+ 94%|█████████▍| 105600/112100 [8:06:15<31:25,  3.45it/s]{'loss': '1.191', 'grad_norm': '1.575', 'learning_rate': '2.92e-06', 'epoch': '94.2'}
+
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+                                                         
+
+ 94%|█████████▍| 105700/112100 [8:06:41<24:08,  4.42it/s]{'loss': '1.192', 'grad_norm': '1.236', 'learning_rate': '2.876e-06', 'epoch': '94.29'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 94%|█████████▍| 105800/112100 [8:07:07<30:12,  3.48it/s]{'loss': '1.192', 'grad_norm': '1.039', 'learning_rate': '2.831e-06', 'epoch': '94.38'}
+
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+                                                         
+
+ 94%|█████████▍| 105900/112100 [8:07:36<26:10,  3.95it/s]{'loss': '1.192', 'grad_norm': '1.157', 'learning_rate': '2.786e-06', 'epoch': '94.47'}
+
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+                                                         
+
+ 95%|█████████▍| 106000/112100 [8:08:06<28:36,  3.55it/s]{'loss': '1.191', 'grad_norm': '1.172', 'learning_rate': '2.742e-06', 'epoch': '94.56'}
+
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+                                                         
+
+ 95%|█████████▍| 106100/112100 [8:08:35<25:04,  3.99it/s]{'loss': '1.192', 'grad_norm': '1.145', 'learning_rate': '2.697e-06', 'epoch': '94.65'}
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+                                                         
+
+ 95%|█████████▍| 106200/112100 [8:09:06<26:57,  3.65it/s]{'loss': '1.192', 'grad_norm': '1.127', 'learning_rate': '2.653e-06', 'epoch': '94.74'}
+
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+                                                         
+
+ 95%|█████████▍| 106300/112100 [8:09:35<27:28,  3.52it/s]{'loss': '1.192', 'grad_norm': '0.9797', 'learning_rate': '2.608e-06', 'epoch': '94.83'}
+
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+                                                         
+
+ 95%|█████████▍| 106400/112100 [8:10:06<27:03,  3.51it/s]{'loss': '1.192', 'grad_norm': '1.439', 'learning_rate': '2.563e-06', 'epoch': '94.92'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 95%|█████████▌| 106500/112100 [8:10:37<38:59,  2.39it/s]{'loss': '1.192', 'grad_norm': '1.086', 'learning_rate': '2.519e-06', 'epoch': '95'}
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+                                                         
+
+ 95%|█████████▌| 106600/112100 [8:11:07<25:19,  3.62it/s]{'loss': '1.192', 'grad_norm': '1.183', 'learning_rate': '2.474e-06', 'epoch': '95.09'}
+
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+                                                         
+
+ 95%|█████████▌| 106700/112100 [8:11:32<21:04,  4.27it/s]{'loss': '1.192', 'grad_norm': '1.301', 'learning_rate': '2.43e-06', 'epoch': '95.18'}
+
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+                                                         
+
+ 95%|█████████▌| 106800/112100 [8:11:58<22:33,  3.92it/s]{'loss': '1.192', 'grad_norm': '0.8925', 'learning_rate': '2.385e-06', 'epoch': '95.27'}
+
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+                                                         
+
+ 95%|█████████▌| 106900/112100 [8:12:26<24:37,  3.52it/s]{'loss': '1.193', 'grad_norm': '1.152', 'learning_rate': '2.34e-06', 'epoch': '95.36'}
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+                                                         
+
+ 95%|█████████▌| 107000/112100 [8:12:56<22:59,  3.70it/s]{'loss': '1.192', 'grad_norm': '1.195', 'learning_rate': '2.296e-06', 'epoch': '95.45'}
+
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+
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+                                                         
+
+ 96%|█████████▌| 107100/112100 [8:13:25<23:58,  3.47it/s]{'loss': '1.191', 'grad_norm': '1.005', 'learning_rate': '2.251e-06', 'epoch': '95.54'}
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.074', 'learning_rate': '2.207e-06', 'epoch': '95.63'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.57it/s]
+
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+                                                         
+
+ 96%|█████████▌| 107300/112100 [8:14:25<22:02,  3.63it/s]{'loss': '1.192', 'grad_norm': '1.237', 'learning_rate': '2.162e-06', 'epoch': '95.72'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 96%|█████████▌| 107400/112100 [8:14:55<18:58,  4.13it/s]{'loss': '1.191', 'grad_norm': '1.277', 'learning_rate': '2.117e-06', 'epoch': '95.81'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+                                                         
+
+ 96%|█████████▌| 107500/112100 [8:15:24<20:12,  3.79it/s]{'loss': '1.192', 'grad_norm': '1.099', 'learning_rate': '2.073e-06', 'epoch': '95.9'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 96%|█████████▌| 107600/112100 [8:15:54<18:51,  3.98it/s]{'loss': '1.192', 'grad_norm': '1.36', 'learning_rate': '2.028e-06', 'epoch': '95.99'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.65it/s]
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+
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+                                                         
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.083', 'learning_rate': '1.983e-06', 'epoch': '96.07'}
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.44it/s]
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+                                                         
+
+ 96%|█████████▌| 107800/112100 [8:16:48<15:48,  4.53it/s]{'loss': '1.191', 'grad_norm': '1.371', 'learning_rate': '1.939e-06', 'epoch': '96.16'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.191', 'grad_norm': '1.446', 'learning_rate': '1.894e-06', 'epoch': '96.25'}
+
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+                                                         
+
+ 96%|█████████▋| 108000/112100 [8:17:47<16:44,  4.08it/s]{'loss': '1.191', 'grad_norm': '1.252', 'learning_rate': '1.85e-06', 'epoch': '96.34'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
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+                                                         
+
+ 96%|█████████▋| 108100/112100 [8:18:17<17:36,  3.79it/s]{'loss': '1.191', 'grad_norm': '1.254', 'learning_rate': '1.805e-06', 'epoch': '96.43'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 97%|█████████▋| 108200/112100 [8:18:45<15:34,  4.18it/s]{'loss': '1.191', 'grad_norm': '1.099', 'learning_rate': '1.76e-06', 'epoch': '96.52'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.49it/s]
+
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+                                                         
+
+ 97%|█████████▋| 108300/112100 [8:19:16<17:17,  3.66it/s]{'loss': '1.191', 'grad_norm': '1.247', 'learning_rate': '1.716e-06', 'epoch': '96.61'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 97%|█████████▋| 108400/112100 [8:19:45<16:19,  3.78it/s]{'loss': '1.192', 'grad_norm': '0.9889', 'learning_rate': '1.672e-06', 'epoch': '96.7'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
+
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+                                                         
+
+ 97%|█████████▋| 108500/112100 [8:20:15<15:45,  3.81it/s]{'loss': '1.192', 'grad_norm': '1.337', 'learning_rate': '1.627e-06', 'epoch': '96.79'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 97%|█████████▋| 108600/112100 [8:20:44<15:08,  3.85it/s]{'loss': '1.193', 'grad_norm': '1.318', 'learning_rate': '1.583e-06', 'epoch': '96.88'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.53it/s]
+
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+                                                         
+
+ 97%|█████████▋| 108700/112100 [8:21:12<12:56,  4.38it/s]{'loss': '1.191', 'grad_norm': '1.257', 'learning_rate': '1.538e-06', 'epoch': '96.97'}
+
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 97%|█████████▋| 108800/112100 [8:21:37<13:18,  4.13it/s]{'loss': '1.192', 'grad_norm': '1.182', 'learning_rate': '1.494e-06', 'epoch': '97.06'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.52it/s]
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+                                                         
+
+ 97%|█████████▋| 108900/112100 [8:22:07<14:50,  3.59it/s]{'loss': '1.191', 'grad_norm': '1.153', 'learning_rate': '1.449e-06', 'epoch': '97.15'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 97%|█████████▋| 109000/112100 [8:22:36<14:21,  3.60it/s]{'loss': '1.192', 'grad_norm': '1.061', 'learning_rate': '1.405e-06', 'epoch': '97.23'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.56it/s]
+
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+                                                         
+
+ 97%|█████████▋| 109100/112100 [8:23:06<14:00,  3.57it/s]{'loss': '1.192', 'grad_norm': '0.9697', 'learning_rate': '1.36e-06', 'epoch': '97.32'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+
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+                                                         
+
+ 97%|█████████▋| 109200/112100 [8:23:35<12:39,  3.82it/s]{'loss': '1.192', 'grad_norm': '1.207', 'learning_rate': '1.315e-06', 'epoch': '97.41'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.58it/s]
+
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+                                                         
+
+ 98%|█████████▊| 109300/112100 [8:24:04<10:56,  4.27it/s]{'loss': '1.192', 'grad_norm': '1.187', 'learning_rate': '1.271e-06', 'epoch': '97.5'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 98%|█████████▊| 109400/112100 [8:24:31<12:01,  3.74it/s]{'loss': '1.191', 'grad_norm': '1.08', 'learning_rate': '1.226e-06', 'epoch': '97.59'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.48it/s]
+
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+                                                         
+
+ 98%|█████████▊| 109500/112100 [8:24:59<10:06,  4.29it/s]{'loss': '1.192', 'grad_norm': '0.9186', 'learning_rate': '1.182e-06', 'epoch': '97.68'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 98%|█████████▊| 109600/112100 [8:25:27<11:05,  3.76it/s]{'loss': '1.192', 'grad_norm': '1.536', 'learning_rate': '1.137e-06', 'epoch': '97.77'}
+
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+                                                         
+
+ 98%|█████████▊| 109700/112100 [8:25:51<07:43,  5.18it/s]{'loss': '1.191', 'grad_norm': '1.359', 'learning_rate': '1.092e-06', 'epoch': '97.86'}
+
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+                                                         
+
+ 98%|█████████▊| 109800/112100 [8:26:14<08:19,  4.61it/s]{'loss': '1.191', 'grad_norm': '1.147', 'learning_rate': '1.048e-06', 'epoch': '97.95'}
+
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+                                                         
+
+ 98%|█████████▊| 109900/112100 [8:26:44<08:48,  4.16it/s]{'loss': '1.191', 'grad_norm': '1.146', 'learning_rate': '1.003e-06', 'epoch': '98.04'}
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+                                                         
+
+ 98%|█████████▊| 110000/112100 [8:27:12<09:32,  3.67it/s]{'loss': '1.191', 'grad_norm': '0.9965', 'learning_rate': '9.585e-07', 'epoch': '98.13'}
+
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+                                                         
+
+ 98%|█████████▊| 110100/112100 [8:27:39<08:05,  4.12it/s]{'loss': '1.191', 'grad_norm': '1.368', 'learning_rate': '9.139e-07', 'epoch': '98.22'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 98%|█████████▊| 110200/112100 [8:28:08<08:36,  3.68it/s]{'loss': '1.191', 'grad_norm': '1.156', 'learning_rate': '8.693e-07', 'epoch': '98.31'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
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+                                                         
+
+ 98%|█████████▊| 110300/112100 [8:28:35<07:13,  4.15it/s]{'loss': '1.191', 'grad_norm': '1.177', 'learning_rate': '8.247e-07', 'epoch': '98.39'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 98%|█████████▊| 110400/112100 [8:29:02<07:38,  3.71it/s]{'loss': '1.192', 'grad_norm': '1.295', 'learning_rate': '7.801e-07', 'epoch': '98.48'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+
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+                                                         
+
+ 99%|█████████▊| 110500/112100 [8:29:31<06:12,  4.29it/s]{'loss': '1.192', 'grad_norm': '1.625', 'learning_rate': '7.355e-07', 'epoch': '98.57'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 99%|█████████▊| 110600/112100 [8:29:58<06:34,  3.80it/s]{'loss': '1.191', 'grad_norm': '1.351', 'learning_rate': '6.909e-07', 'epoch': '98.66'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.54it/s]
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+                                                         
+
+ 99%|█████████▉| 110700/112100 [8:30:21<04:08,  5.64it/s]{'loss': '1.192', 'grad_norm': '1.449', 'learning_rate': '6.463e-07', 'epoch': '98.75'}
+
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+                                                         
+
+ 99%|█████████▉| 110800/112100 [8:30:46<05:31,  3.92it/s]{'loss': '1.193', 'grad_norm': '1.344', 'learning_rate': '6.017e-07', 'epoch': '98.84'}
+
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+                                                         
+
+ 99%|█████████▉| 110900/112100 [8:31:13<04:27,  4.48it/s]{'loss': '1.191', 'grad_norm': '1.232', 'learning_rate': '5.571e-07', 'epoch': '98.93'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 99%|█████████▉| 111000/112100 [8:31:44<04:44,  3.87it/s]{'loss': '1.191', 'grad_norm': '1.274', 'learning_rate': '5.125e-07', 'epoch': '99.02'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]
+
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+                                                         
+
+ 99%|█████████▉| 111100/112100 [8:32:11<04:08,  4.02it/s]{'loss': '1.191', 'grad_norm': '1.02', 'learning_rate': '4.679e-07', 'epoch': '99.11'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+                                                         
+
+ 99%|█████████▉| 111200/112100 [8:32:39<03:45,  3.99it/s]{'loss': '1.191', 'grad_norm': '1.19', 'learning_rate': '4.233e-07', 'epoch': '99.2'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.51it/s]
+
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+                                                         
+
+ 99%|█████████▉| 111300/112100 [8:33:06<03:20,  3.99it/s]{'loss': '1.191', 'grad_norm': '1.181', 'learning_rate': '3.787e-07', 'epoch': '99.29'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+ 99%|█████████▉| 111400/112100 [8:33:35<02:58,  3.93it/s]{'loss': '1.191', 'grad_norm': '1.096', 'learning_rate': '3.341e-07', 'epoch': '99.38'}
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
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+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.63it/s]
+
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+                                                         
+
+ 99%|█████████▉| 111500/112100 [8:34:02<02:29,  4.02it/s]{'loss': '1.191', 'grad_norm': '1.158', 'learning_rate': '2.895e-07', 'epoch': '99.46'}
+
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+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
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+                                                         
+
+100%|█████████▉| 111600/112100 [8:34:30<01:41,  4.93it/s]{'loss': '1.192', 'grad_norm': '1.252', 'learning_rate': '2.449e-07', 'epoch': '99.55'}
+
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+                                                         
+
+100%|█████████▉| 111700/112100 [8:34:52<01:21,  4.93it/s]{'loss': '1.191', 'grad_norm': '1.303', 'learning_rate': '2.003e-07', 'epoch': '99.64'}
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+                                                         
+
+100%|█████████▉| 111800/112100 [8:35:17<01:09,  4.34it/s]{'loss': '1.191', 'grad_norm': '0.9271', 'learning_rate': '1.557e-07', 'epoch': '99.73'}
+
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+                                                         
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+                                                         
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+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.192', 'grad_norm': '1.194', 'learning_rate': '6.646e-08', 'epoch': '99.91'}
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+                                                         
+
+100%|██████████| 112100/112100 [8:36:40<00:00,  3.93it/s]
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]{'loss': '1.191', 'grad_norm': '1.93', 'learning_rate': '2.186e-08', 'epoch': '100'}
+
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.60it/s]
+
+
+Writing model shards:   0%|          | 0/1 [00:00<?, ?it/s]
+
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.28it/s]
+Writing model shards: 100%|██████████| 1/1 [00:00<00:00,  1.28it/s]
+
+                                                         
+
+100%|██████████| 112100/112100 [8:36:45<00:00,  3.93it/s]
+100%|██████████| 112100/112100 [8:36:45<00:00,  3.62it/s]
+{'train_runtime': '3.101e+04', 'train_samples_per_second': '115.6', 'train_steps_per_second': '3.616', 'train_loss': '1.205', 'epoch': '100'}
+Copying artefacts from: best-disc-model
+Copying artefacts from: mean-best-disc-model
+Copying artefacts from: not-best-disc-model
+Copying artefacts from: last-epoch-model
+[benchmark_cli] Training done, model saved -> /work/output-SpecializedModels/c20/realtabformer/rtf-c20-20260329_231509/models_100epochs
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/_tabddpm_train.py b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/_tabddpm_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..e448a3ecb38cdc684ff88c534f44b79d9aa17221
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/_tabddpm_train.py
@@ -0,0 +1,32 @@
+import os, sys, subprocess
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Write a wrapper that patches collections.Sequence (removed in Python 3.10+)
+# before running pipeline.py - needed because skorch uses old API
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+with open(wrapper, "w") as f:
+    f.write(
+        "import collections, collections.abc\n"
+        "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+        "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+        "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+        "import sys, runpy\n"
+        "sys.argv = sys.argv[1:]\n"
+        "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+    )
+
+print(f"[TabDDPM] Training, config=/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/config.toml")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/config.toml",
+     "--train"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+print("[TabDDPM] Training complete")
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/config.toml b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/config.toml
new file mode 100644
index 0000000000000000000000000000000000000000..26c3c1c5d47924e3abf74fb4ea09f16c1e76f8a4
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/config.toml
@@ -0,0 +1,39 @@
+seed = 0
+parent_dir = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/output"
+real_data_path = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data"
+model_type = "mlp"
+num_numerical_features = 6
+device = "cuda:0"
+
+[model_params]
+d_in = 6
+num_classes = 3
+is_y_cond = true
+
+[model_params.rtdl_params]
+d_layers = [256, 256]
+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
+steps = 5000
+lr = 0.001
+weight_decay = 0.0
+batch_size = 256
+
+[train.T]
+seed = 0
+normalization = "quantile"
+num_nan_policy = "__none__"
+cat_nan_policy = "__none__"
+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
+
+[sample]
+num_samples = 1000
+batch_size = 1000
+seed = 0
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data/X_num_test.npy b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data/X_num_test.npy
new file mode 100644
index 0000000000000000000000000000000000000000..a7abe6def558144493058514bd38728dfb8e3806
Binary files /dev/null and b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data/X_num_test.npy differ
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data/info.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data/info.json
new file mode 100644
index 0000000000000000000000000000000000000000..1e3722aa2a09d6a7bfdff97b71ac3a85667d1d45
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data/info.json
@@ -0,0 +1,29 @@
+{
+  "name": "benchmark_dataset",
+  "task_type": "multiclass",
+  "n_num_features": 6,
+  "n_cat_features": 0,
+  "train_size": 35855,
+  "num_col_idx": [
+    0,
+    1,
+    2,
+    3,
+    4,
+    5
+  ],
+  "cat_col_idx": [],
+  "target_col_idx": [
+    6
+  ],
+  "column_names": [
+    "white_piece0_strength",
+    "white_piece0_file",
+    "white_piece0_rank",
+    "black_piece0_strength",
+    "black_piece0_file",
+    "black_piece0_rank",
+    "class"
+  ],
+  "num_classes": 3
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data/y_test.npy b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data/y_test.npy
new file mode 100644
index 0000000000000000000000000000000000000000..42d012cd50e4e57a95e2126322410a94b6f3c16e
Binary files /dev/null and b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/data/y_test.npy differ
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/train_20260319_072624.log b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/train_20260319_072624.log
new file mode 100644
index 0000000000000000000000000000000000000000..2e0b454d5bc44408e292a150427e386347bd65bb
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/train_20260319_072624.log
@@ -0,0 +1,26 @@
+/opt/conda/lib/python3.11/site-packages/skorch/__init__.py:6: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
+  import pkg_resources
+[0]
+6
+{'d_in': 6, 'num_classes': 3, 'is_y_cond': True, 'rtdl_params': {'d_layers': [256, 256], 'dropout': 0.0}}
+mlp
+Traceback (most recent call last):
+  File "/workspace/tabddpm/code/_compat_run.py", line 6, in <module>
+    runpy.run_path(sys.argv[0], run_name='__main__')
+  File "<frozen runpy>", line 291, in run_path
+  File "<frozen runpy>", line 98, in _run_module_code
+  File "<frozen runpy>", line 88, in _run_code
+  File "scripts/pipeline.py", line 112, in <module>
+    main()
+  File "scripts/pipeline.py", line 48, in main
+    train(
+  File "/workspace/tabddpm/code/scripts/train.py", line 154, in train
+    trainer.run_loop()
+  File "/workspace/tabddpm/code/scripts/train.py", line 53, in run_loop
+    x, out_dict = next(self.train_iter)
+                  ^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/tabddpm/code/lib/data.py", line 605, in prepare_fast_dataloader
+    y = torch.from_numpy(D.y[split])
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+TypeError: can't convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint64, uint32, uint16, uint8, and bool.
+[TabDDPM] Training, config=/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_072621/config.toml
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/_tabddpm_train.py b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/_tabddpm_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..039e8911afd86b2b23bddda8ae97d1f8822c0fc2
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/_tabddpm_train.py
@@ -0,0 +1,32 @@
+import os, sys, subprocess
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Write a wrapper that patches collections.Sequence (removed in Python 3.10+)
+# before running pipeline.py - needed because skorch uses old API
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+with open(wrapper, "w") as f:
+    f.write(
+        "import collections, collections.abc\n"
+        "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+        "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+        "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+        "import sys, runpy\n"
+        "sys.argv = sys.argv[1:]\n"
+        "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+    )
+
+print(f"[TabDDPM] Training, config=/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/config.toml")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/config.toml",
+     "--train"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+print("[TabDDPM] Training complete")
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/config.toml b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/config.toml
new file mode 100644
index 0000000000000000000000000000000000000000..541374b546222c4a5a90cea30d9e863c349f7242
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/config.toml
@@ -0,0 +1,39 @@
+seed = 0
+parent_dir = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/output"
+real_data_path = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/data"
+model_type = "mlp"
+num_numerical_features = 6
+device = "cuda:0"
+
+[model_params]
+d_in = 6
+num_classes = 3
+is_y_cond = true
+
+[model_params.rtdl_params]
+d_layers = [256, 256]
+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
+steps = 5000
+lr = 0.001
+weight_decay = 0.0
+batch_size = 256
+
+[train.T]
+seed = 0
+normalization = "quantile"
+num_nan_policy = "__none__"
+cat_nan_policy = "__none__"
+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
+
+[sample]
+num_samples = 1000
+batch_size = 1000
+seed = 0
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/train_20260319_224929.log b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/train_20260319_224929.log
new file mode 100644
index 0000000000000000000000000000000000000000..d9d9e230e09c3c5c5da5d75d2bf0a6c30b40c9cc
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/train_20260319_224929.log
@@ -0,0 +1,26 @@
+/opt/conda/lib/python3.11/site-packages/skorch/__init__.py:6: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
+  import pkg_resources
+Traceback (most recent call last):
+  File "/workspace/tabddpm/code/_compat_run.py", line 6, in <module>
+    runpy.run_path(sys.argv[0], run_name='__main__')
+[0]
+6
+{'d_in': 6, 'num_classes': 3, 'is_y_cond': True, 'rtdl_params': {'d_layers': [256, 256], 'dropout': 0.0}}
+mlp
+  File "<frozen runpy>", line 291, in run_path
+  File "<frozen runpy>", line 98, in _run_module_code
+  File "<frozen runpy>", line 88, in _run_code
+  File "scripts/pipeline.py", line 112, in <module>
+    main()
+  File "scripts/pipeline.py", line 48, in main
+    train(
+  File "/workspace/tabddpm/code/scripts/train.py", line 154, in train
+    trainer.run_loop()
+  File "/workspace/tabddpm/code/scripts/train.py", line 53, in run_loop
+    x, out_dict = next(self.train_iter)
+                  ^^^^^^^^^^^^^^^^^^^^^
+  File "/workspace/tabddpm/code/lib/data.py", line 605, in prepare_fast_dataloader
+    y = torch.from_numpy(D.y[split])
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+TypeError: can't convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint64, uint32, uint16, uint8, and bool.
+[TabDDPM] Training, config=/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260319_224926/config.toml
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/_tabddpm_sample.py b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/_tabddpm_sample.py
new file mode 100644
index 0000000000000000000000000000000000000000..8856205cba6fa2105257621d7d2eb4bcfbf7d2d5
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/_tabddpm_sample.py
@@ -0,0 +1,67 @@
+import os, sys, subprocess, json
+import numpy as np
+import pandas as pd
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Reuse the compat wrapper (patches collections.Sequence for skorch)
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+if not os.path.exists(wrapper):
+    with open(wrapper, "w") as f:
+        f.write(
+            "import collections, collections.abc\n"
+            "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+            "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+            "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+            "import sys, runpy\n"
+            "sys.argv = sys.argv[1:]\n"
+            "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+        )
+
+print(f"[TabDDPM] Sampling 1000 rows")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/config.toml",
+     "--sample"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+
+# 将 .npy 输出转为 CSV
+work_dir = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520"
+info_path = os.path.join(work_dir, "data", "info.json")
+with open(info_path) as f:
+    info = json.load(f)
+
+output_dir = os.path.join(work_dir, "output")
+col_names = info.get("column_names", [])
+
+parts = []
+x_num_path = os.path.join(output_dir, "X_num_train.npy")
+x_cat_path = os.path.join(output_dir, "X_cat_train.npy")
+y_path = os.path.join(output_dir, "y_train.npy")
+
+if os.path.exists(x_num_path):
+    parts.append(np.load(x_num_path, allow_pickle=True))
+if os.path.exists(x_cat_path):
+    parts.append(np.load(x_cat_path, allow_pickle=True).astype(float))
+if os.path.exists(y_path):
+    y = np.load(y_path, allow_pickle=True)
+    parts.append(y.reshape(-1, 1) if y.ndim == 1 else y)
+
+if parts:
+    combined = np.concatenate(parts, axis=1)
+    if col_names and len(col_names) == combined.shape[1]:
+        df = pd.DataFrame(combined, columns=col_names)
+    else:
+        df = pd.DataFrame(combined)
+    df.to_csv("/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/tabddpm-c20-1000-20260321_150712.csv", index=False)
+    print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/tabddpm-c20-1000-20260321_150712.csv")
+else:
+    print("[TabDDPM] WARNING: No output .npy files found")
+    sys.exit(1)
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/_tabddpm_train.py b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/_tabddpm_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..19c70f7cec36c03dc315d15803bd38947bb3ace7
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/_tabddpm_train.py
@@ -0,0 +1,32 @@
+import os, sys, subprocess
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Write a wrapper that patches collections.Sequence (removed in Python 3.10+)
+# before running pipeline.py - needed because skorch uses old API
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+with open(wrapper, "w") as f:
+    f.write(
+        "import collections, collections.abc\n"
+        "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+        "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+        "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+        "import sys, runpy\n"
+        "sys.argv = sys.argv[1:]\n"
+        "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+    )
+
+print(f"[TabDDPM] Training, config=/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/config.toml")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/config.toml",
+     "--train"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+print("[TabDDPM] Training complete")
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/config.toml b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/config.toml
new file mode 100644
index 0000000000000000000000000000000000000000..7b6d8fbea7fc233ee2ac556411fb330645731689
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/config.toml
@@ -0,0 +1,39 @@
+seed = 0
+parent_dir = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/output"
+real_data_path = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/data"
+model_type = "mlp"
+num_numerical_features = 6
+device = "cuda:0"
+
+[model_params]
+d_in = 6
+num_classes = 3
+is_y_cond = true
+
+[model_params.rtdl_params]
+d_layers = [256, 256]
+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
+steps = 5000
+lr = 0.001
+weight_decay = 0.0
+batch_size = 256
+
+[train.T]
+seed = 0
+normalization = "quantile"
+num_nan_policy = "__none__"
+cat_nan_policy = "__none__"
+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
+
+[sample]
+num_samples = 1000
+batch_size = 1000
+seed = 0
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/gen_20260321_150712.log b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/gen_20260321_150712.log
new file mode 100644
index 0000000000000000000000000000000000000000..f0151e33939dcfd1436ff089ca8abcba26b13751
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/gen_20260321_150712.log
@@ -0,0 +1,1008 @@
+/opt/conda/lib/python3.11/site-packages/skorch/__init__.py:6: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
+  import pkg_resources
+mlp
+Sample timestep  999
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+Sample timestep   10
+Sample timestep    9
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+Sample timestep    6
+Sample timestep    5
+Sample timestep    4
+Sample timestep    3
+Sample timestep    2
+Sample timestep    1
+Sample timestep    0
+Discrete cols: [0, 1, 2, 3, 4, 5]
+Num shape:  (1000, 6)
+Elapsed time: 0:00:11
+[TabDDPM] Sampling 1000 rows
+[TabDDPM] Saved 1000 rows -> /work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/tabddpm-c20-1000-20260321_150712.csv
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/input_snapshot.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/input_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..d9b170e1de3486ebeaf215f5e9967caec8638693
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/input_snapshot.json
@@ -0,0 +1,36 @@
+{
+  "dataset_id": "c20",
+  "model": "tabddpm",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-train.csv",
+      "exists": true,
+      "size": 537948,
+      "sha256": "7b491c9989a22d06db0c24422e76bf1d73173a7ba1760d5a3c4e5768c868ac21"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-val.csv",
+      "exists": true,
+      "size": 67338,
+      "sha256": "82d69efb2fbd8ddf6e8d77d9070b3d299f619fded74e2956d3af4b34a9c95a75"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-test.csv",
+      "exists": true,
+      "size": 67368,
+      "sha256": "ab311b2ccc419e2b1423bd27d4079912f464405ef8d37cd87e73ad147ed787ec"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c20/c20-dataset_profile.json",
+      "exists": true,
+      "size": 3686,
+      "sha256": "64a935250a31399f41982c61828d40ab90791bab84e8dc6201dbdfa4508092b8"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c20/c20-dataset_contract_v1.json",
+      "exists": true,
+      "size": 3867,
+      "sha256": "78c743a19951022e3cbae86814578ff8723146c3d216423edc4b94e1b233ad27"
+    }
+  }
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/runtime_result.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/runtime_result.json
new file mode 100644
index 0000000000000000000000000000000000000000..531ed14ff18fa3ce9425e2a5c7704a8c90d147c3
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/runtime_result.json
@@ -0,0 +1,15 @@
+{
+  "dataset_id": "c20",
+  "model": "tabddpm",
+  "run_id": "tabddpm-c20-20260321_150520",
+  "public_gate_status": "pass",
+  "adapter_ready_status": "pass",
+  "train_status": "success",
+  "generate_status": "success",
+  "reason_code": null,
+  "reason_detail": null,
+  "artifacts": {
+    "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/tabddpm-c20-1000-20260321_150712.csv",
+    "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520"
+  }
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/train_20260321_150520.log b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/train_20260321_150520.log
new file mode 100644
index 0000000000000000000000000000000000000000..d76cec4117c3d329152b3833c69285014e1d2dc3
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/train_20260321_150520.log
@@ -0,0 +1,19 @@
+/opt/conda/lib/python3.11/site-packages/skorch/__init__.py:6: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
+  import pkg_resources
+[0]
+6
+{'d_in': 6, 'num_classes': 3, 'is_y_cond': True, 'rtdl_params': {'d_layers': [256, 256], 'dropout': 0.0}}
+mlp
+Step 500/5000 MLoss: 0.0 GLoss: 0.5155 Sum: 0.5155
+Step 1000/5000 MLoss: 0.0 GLoss: 0.4573 Sum: 0.4573
+Step 1500/5000 MLoss: 0.0 GLoss: 0.4333 Sum: 0.4333
+Step 2000/5000 MLoss: 0.0 GLoss: 0.4251 Sum: 0.4251
+Step 2500/5000 MLoss: 0.0 GLoss: 0.4261 Sum: 0.4261
+Step 3000/5000 MLoss: 0.0 GLoss: 0.4159 Sum: 0.4159
+Step 3500/5000 MLoss: 0.0 GLoss: 0.4096 Sum: 0.4096
+Step 4000/5000 MLoss: 0.0 GLoss: 0.4023 Sum: 0.4023
+Step 4500/5000 MLoss: 0.0 GLoss: 0.3999 Sum: 0.3999
+Step 5000/5000 MLoss: 0.0 GLoss: 0.3928 Sum: 0.3928
+Elapsed time: 0:01:38
+[TabDDPM] Training, config=/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260321_150520/config.toml
+[TabDDPM] Training complete
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/_tabddpm_sample.py b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/_tabddpm_sample.py
new file mode 100644
index 0000000000000000000000000000000000000000..f6798f2c9003423b1b18a87a243026aa561dbf43
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/_tabddpm_sample.py
@@ -0,0 +1,67 @@
+import os, sys, subprocess, json
+import numpy as np
+import pandas as pd
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Reuse the compat wrapper (patches collections.Sequence for skorch)
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+if not os.path.exists(wrapper):
+    with open(wrapper, "w") as f:
+        f.write(
+            "import collections, collections.abc\n"
+            "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+            "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+            "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+            "import sys, runpy\n"
+            "sys.argv = sys.argv[1:]\n"
+            "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+        )
+
+print(f"[TabDDPM] Sampling 35855 rows")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config_sample_20260424_033931.toml",
+     "--sample"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+
+# 将 .npy 输出转为 CSV
+work_dir = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725"
+info_path = os.path.join(work_dir, "data", "info.json")
+with open(info_path) as f:
+    info = json.load(f)
+
+output_dir = os.path.join(work_dir, "output")
+col_names = info.get("column_names", [])
+
+parts = []
+x_num_path = os.path.join(output_dir, "X_num_train.npy")
+x_cat_path = os.path.join(output_dir, "X_cat_train.npy")
+y_path = os.path.join(output_dir, "y_train.npy")
+
+if os.path.exists(x_num_path):
+    parts.append(np.load(x_num_path, allow_pickle=True))
+if os.path.exists(x_cat_path):
+    parts.append(np.load(x_cat_path, allow_pickle=True).astype(float))
+if os.path.exists(y_path):
+    y = np.load(y_path, allow_pickle=True)
+    parts.append(y.reshape(-1, 1) if y.ndim == 1 else y)
+
+if parts:
+    combined = np.concatenate(parts, axis=1)
+    if col_names and len(col_names) == combined.shape[1]:
+        df = pd.DataFrame(combined, columns=col_names)
+    else:
+        df = pd.DataFrame(combined)
+    df.to_csv("/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/tabddpm-c20-35855-20260424_033931.csv", index=False)
+    print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/tabddpm-c20-35855-20260424_033931.csv")
+else:
+    print("[TabDDPM] WARNING: No output .npy files found")
+    sys.exit(1)
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/_tabddpm_train.py b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/_tabddpm_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..d1c0f1d905b999709916b652045a91363c1e7410
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/_tabddpm_train.py
@@ -0,0 +1,32 @@
+import os, sys, subprocess
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Write a wrapper that patches collections.Sequence (removed in Python 3.10+)
+# before running pipeline.py - needed because skorch uses old API
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+with open(wrapper, "w") as f:
+    f.write(
+        "import collections, collections.abc\n"
+        "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+        "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+        "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+        "import sys, runpy\n"
+        "sys.argv = sys.argv[1:]\n"
+        "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+    )
+
+print(f"[TabDDPM] Training, config=/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config.toml")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config.toml",
+     "--train"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+print("[TabDDPM] Training complete")
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config.toml b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config.toml
new file mode 100644
index 0000000000000000000000000000000000000000..3e24687ca7ebe2b0c7622b8bf59de9845868849a
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config.toml
@@ -0,0 +1,39 @@
+seed = 0
+parent_dir = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/output"
+real_data_path = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/data"
+model_type = "mlp"
+num_numerical_features = 6
+device = "cuda:0"
+
+[model_params]
+d_in = 6
+num_classes = 3
+is_y_cond = true
+
+[model_params.rtdl_params]
+d_layers = [256, 256]
+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
+steps = 5000
+lr = 0.001
+weight_decay = 0.0
+batch_size = 256
+
+[train.T]
+seed = 0
+normalization = "quantile"
+num_nan_policy = "__none__"
+cat_nan_policy = "__none__"
+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
+
+[sample]
+num_samples = 1000
+batch_size = 1000
+seed = 0
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config_sample_20260424_033931.toml b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config_sample_20260424_033931.toml
new file mode 100644
index 0000000000000000000000000000000000000000..8c3bd9623f95b39bf451ce6c0eb01d0ce0066a9f
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config_sample_20260424_033931.toml
@@ -0,0 +1,39 @@
+seed = 0
+parent_dir = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/output"
+real_data_path = "/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/data"
+model_type = "mlp"
+num_numerical_features = 6
+device = "cuda:0"
+
+[model_params]
+d_in = 6
+num_classes = 3
+is_y_cond = true
+
+[model_params.rtdl_params]
+d_layers = [256, 256]
+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
+steps = 5000
+lr = 0.001
+weight_decay = 0.0
+batch_size = 256
+
+[train.T]
+seed = 0
+normalization = "quantile"
+num_nan_policy = "__none__"
+cat_nan_policy = "__none__"
+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
+
+[sample]
+num_samples = 35855
+batch_size = 1000
+seed = 0
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/gen_20260424_033931.log b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/gen_20260424_033931.log
new file mode 100644
index 0000000000000000000000000000000000000000..f613d58f914af6d5047b65b9fb9d7ac8eb75d6c4
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/gen_20260424_033931.log
@@ -0,0 +1,36006 @@
+mlp
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+Discrete cols: [0, 1, 2, 3, 4, 5]
+Num shape:  (35855, 6)
+Elapsed time: 0:11:01
+[TabDDPM] Sampling 35855 rows
+[TabDDPM] Saved 35855 rows -> /work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/tabddpm-c20-35855-20260424_033931.csv
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/input_snapshot.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/input_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..d9b170e1de3486ebeaf215f5e9967caec8638693
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/input_snapshot.json
@@ -0,0 +1,36 @@
+{
+  "dataset_id": "c20",
+  "model": "tabddpm",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-train.csv",
+      "exists": true,
+      "size": 537948,
+      "sha256": "7b491c9989a22d06db0c24422e76bf1d73173a7ba1760d5a3c4e5768c868ac21"
+    },
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+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-val.csv",
+      "exists": true,
+      "size": 67338,
+      "sha256": "82d69efb2fbd8ddf6e8d77d9070b3d299f619fded74e2956d3af4b34a9c95a75"
+    },
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+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-test.csv",
+      "exists": true,
+      "size": 67368,
+      "sha256": "ab311b2ccc419e2b1423bd27d4079912f464405ef8d37cd87e73ad147ed787ec"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c20/c20-dataset_profile.json",
+      "exists": true,
+      "size": 3686,
+      "sha256": "64a935250a31399f41982c61828d40ab90791bab84e8dc6201dbdfa4508092b8"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c20/c20-dataset_contract_v1.json",
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+      "sha256": "78c743a19951022e3cbae86814578ff8723146c3d216423edc4b94e1b233ad27"
+    }
+  }
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/runtime_result.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/runtime_result.json
new file mode 100644
index 0000000000000000000000000000000000000000..cba48bb11a4f54acc19742ce1e92ce98e7cd92fb
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/runtime_result.json
@@ -0,0 +1,15 @@
+{
+  "dataset_id": "c20",
+  "model": "tabddpm",
+  "run_id": "tabddpm-c20-20260424_033725",
+  "public_gate_status": "pass",
+  "adapter_ready_status": "pass",
+  "train_status": "success",
+  "generate_status": "success",
+  "reason_code": null,
+  "reason_detail": null,
+  "artifacts": {
+    "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/tabddpm-c20-35855-20260424_033931.csv",
+    "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725"
+  }
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/train_20260424_033725.log b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/train_20260424_033725.log
new file mode 100644
index 0000000000000000000000000000000000000000..69b8e118da51c8d327d0f4ffb241b71fdd7bb077
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/train_20260424_033725.log
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+Step 500/5000 MLoss: 0.0 GLoss: 0.5155 Sum: 0.5155
+Step 1000/5000 MLoss: 0.0 GLoss: 0.4573 Sum: 0.4573
+Step 1500/5000 MLoss: 0.0 GLoss: 0.4333 Sum: 0.4333
+Step 2000/5000 MLoss: 0.0 GLoss: 0.4251 Sum: 0.4251
+Step 2500/5000 MLoss: 0.0 GLoss: 0.4261 Sum: 0.4261
+Step 3000/5000 MLoss: 0.0 GLoss: 0.4159 Sum: 0.4159
+Step 3500/5000 MLoss: 0.0 GLoss: 0.4096 Sum: 0.4096
+Step 4000/5000 MLoss: 0.0 GLoss: 0.4023 Sum: 0.4023
+Step 4500/5000 MLoss: 0.0 GLoss: 0.3999 Sum: 0.3999
+Step 5000/5000 MLoss: 0.0 GLoss: 0.3928 Sum: 0.3928
+Elapsed time: 0:01:57
+[TabDDPM] Training, config=/work/output-SpecializedModels/c20/tabddpm/tabddpm-c20-20260424_033725/config.toml
+[TabDDPM] Training complete
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/X_cat_train.npy b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/X_cat_train.npy
new file mode 100644
index 0000000000000000000000000000000000000000..3b810787afb2258bdeb992731460979460f32908
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/info.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/info.json
new file mode 100644
index 0000000000000000000000000000000000000000..913d80ba82cca8105507df3cb3b9b4edb492304c
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/info.json
@@ -0,0 +1,93 @@
+{
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+  ],
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+  "test_num": 4483,
+  "header": 0,
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\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/test.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/test.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ea90ac39e7f07dc9e421f5b078baccc412d1118e
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+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/test.csv
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/train.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/train.csv
new file mode 100644
index 0000000000000000000000000000000000000000..6e9bc2b9a9971f1cad46c9cb7f051e19b4c8dfb5
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/data/tabsyn_c20/train.csv
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/synthetic/tabsyn_c20/real.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/synthetic/tabsyn_c20/real.csv
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index 0000000000000000000000000000000000000000..6e9bc2b9a9971f1cad46c9cb7f051e19b4c8dfb5
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/synthetic/tabsyn_c20/real.csv
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/train_20260421_023649.log b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/train_20260421_023649.log
new file mode 100644
index 0000000000000000000000000000000000000000..ab27d7f90a38967cfce7317b8b80cd8fa1faab13
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260421_023648/train_20260421_023649.log
@@ -0,0 +1,46144 @@
+[TabSyn] Step 1/2: Training VAE in /workspace/tabsyn, dataname=tabsyn_c20
+/opt/conda/lib/python3.11/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
+  import pynvml  # type: ignore[import]
+No NaNs in numerical features, skipping
+self.category_embeddings.weight.shape=torch.Size([3, 4])
+self.category_embeddings.weight.shape=torch.Size([3, 4])
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1/4000:  10%|█         | 1/10 [00:01<00:17,  2.00s/it]
+Epoch 1/4000:  40%|████      | 4/10 [00:02<00:02,  2.43it/s]
+Epoch 1/4000:  80%|████████  | 8/10 [00:02<00:00,  5.52it/s]
+Epoch 1/4000: 100%|██████████| 10/10 [00:02<00:00,  4.18it/s]
+epoch: 0, beta = 0.010000, Train MSE: 4.901596, Train CE:1.207811, Train KL:0.526602, Val MSE:4.106030, Val CE:1.115879, Train ACC:0.448445, Val ACC:0.475128
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2/4000:  10%|█         | 1/10 [00:00<00:04,  1.95it/s]
+Epoch 2/4000:  40%|████      | 4/10 [00:00<00:00,  7.80it/s]
+Epoch 2/4000:  80%|████████  | 8/10 [00:00<00:00, 14.06it/s]
+Epoch 2/4000: 100%|██████████| 10/10 [00:00<00:00, 10.57it/s]
+epoch: 1, beta = 0.010000, Train MSE: 3.705148, Train CE:1.062934, Train KL:0.743530, Val MSE:3.222354, Val CE:0.997019, Train ACC:0.514689, Val ACC:0.511934
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3/4000:  10%|█         | 1/10 [00:00<00:04,  1.89it/s]
+Epoch 3/4000:  40%|████      | 4/10 [00:00<00:00,  7.61it/s]
+Epoch 3/4000:  80%|████████  | 8/10 [00:00<00:00, 14.00it/s]
+Epoch 3/4000: 100%|██████████| 10/10 [00:00<00:00, 10.42it/s]
+epoch: 2, beta = 0.010000, Train MSE: 2.899971, Train CE:0.959701, Train KL:1.126569, Val MSE:2.500272, Val CE:0.913703, Train ACC:0.534562, Val ACC:0.514611
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 4/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 4/4000:  10%|█         | 1/10 [00:00<00:04,  2.07it/s]
+Epoch 4/4000:  40%|████      | 4/10 [00:00<00:00,  7.91it/s]
+Epoch 4/4000:  80%|████████  | 8/10 [00:00<00:00, 14.24it/s]
+Epoch 4/4000: 100%|██████████| 10/10 [00:00<00:00, 10.64it/s]
+epoch: 3, beta = 0.010000, Train MSE: 2.242299, Train CE:0.864372, Train KL:1.497838, Val MSE:1.845225, Val CE:0.810930, Train ACC:0.537154, Val ACC:0.546509
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 5/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 5/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 5/4000:  40%|████      | 4/10 [00:00<00:00,  7.49it/s]
+Epoch 5/4000:  80%|████████  | 8/10 [00:00<00:00, 13.85it/s]
+Epoch 5/4000: 100%|██████████| 10/10 [00:00<00:00, 10.41it/s]
+epoch: 4, beta = 0.010000, Train MSE: 1.565262, Train CE:0.781952, Train KL:1.918068, Val MSE:1.225390, Val CE:0.744811, Train ACC:0.606855, Val ACC:0.607183
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 6/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 6/4000:  40%|████      | 4/10 [00:00<00:00,  7.52it/s]
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+Epoch 6/4000: 100%|██████████| 10/10 [00:00<00:00, 10.40it/s]
+epoch: 5, beta = 0.010000, Train MSE: 1.036388, Train CE:0.714812, Train KL:2.330494, Val MSE:0.826389, Val CE:0.684134, Train ACC:0.622120, Val ACC:0.611198
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 7/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 7/4000:  40%|████      | 4/10 [00:00<00:00,  7.73it/s]
+Epoch 7/4000:  80%|████████  | 8/10 [00:00<00:00, 14.22it/s]
+Epoch 7/4000: 100%|██████████| 10/10 [00:00<00:00, 10.60it/s]
+epoch: 6, beta = 0.010000, Train MSE: 0.707691, Train CE:0.663305, Train KL:2.682426, Val MSE:0.574483, Val CE:0.640720, Train ACC:0.620968, Val ACC:0.619897
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 8/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 8/4000:  10%|█         | 1/10 [00:00<00:04,  2.01it/s]
+Epoch 8/4000:  40%|████      | 4/10 [00:00<00:00,  7.97it/s]
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+Epoch 8/4000: 100%|██████████| 10/10 [00:00<00:00, 10.90it/s]
+epoch: 7, beta = 0.010000, Train MSE: 0.493025, Train CE:0.615452, Train KL:2.961778, Val MSE:0.401116, Val CE:0.582892, Train ACC:0.678571, Val ACC:0.695516
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 9/4000: 100%|██████████| 10/10 [00:01<00:00,  9.69it/s]
+epoch: 8, beta = 0.010000, Train MSE: 0.340955, Train CE:0.546885, Train KL:3.135916, Val MSE:0.273632, Val CE:0.496776, Train ACC:0.852823, Val ACC:0.863930
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 10/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 10/4000: 100%|██████████| 10/10 [00:00<00:00, 10.36it/s]
+epoch: 9, beta = 0.010000, Train MSE: 0.232969, Train CE:0.439743, Train KL:3.322772, Val MSE:0.193523, Val CE:0.367142, Train ACC:0.974654, Val ACC:0.971894
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 11/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 11/4000: 100%|██████████| 10/10 [00:00<00:00, 10.31it/s]
+epoch: 10, beta = 0.010000, Train MSE: 0.167940, Train CE:0.309639, Train KL:3.584318, Val MSE:0.144938, Val CE:0.245325, Train ACC:0.995680, Val ACC:0.995539
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 12/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 12/4000: 100%|██████████| 10/10 [00:00<00:00, 10.17it/s]
+epoch: 11, beta = 0.010000, Train MSE: 0.129657, Train CE:0.202253, Train KL:3.803305, Val MSE:0.114505, Val CE:0.157128, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 13/4000: 100%|██████████| 10/10 [00:00<00:00, 10.05it/s]
+epoch: 12, beta = 0.010000, Train MSE: 0.105541, Train CE:0.129869, Train KL:3.950776, Val MSE:0.094653, Val CE:0.102217, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 14/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 14/4000: 100%|██████████| 10/10 [00:00<00:00, 10.11it/s]
+epoch: 13, beta = 0.010000, Train MSE: 0.087864, Train CE:0.085901, Train KL:4.036649, Val MSE:0.078361, Val CE:0.069626, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 15/4000: 100%|██████████| 10/10 [00:00<00:00, 10.38it/s]
+epoch: 14, beta = 0.010000, Train MSE: 0.073349, Train CE:0.059925, Train KL:4.074745, Val MSE:0.065942, Val CE:0.050223, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 16/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 16/4000: 100%|██████████| 10/10 [00:00<00:00, 11.13it/s]
+epoch: 15, beta = 0.010000, Train MSE: 0.062039, Train CE:0.044230, Train KL:4.087151, Val MSE:0.056374, Val CE:0.038245, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 17/4000: 100%|██████████| 10/10 [00:00<00:00, 10.79it/s]
+epoch: 16, beta = 0.010000, Train MSE: 0.053521, Train CE:0.034193, Train KL:4.075723, Val MSE:0.049168, Val CE:0.030142, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+epoch: 17, beta = 0.010000, Train MSE: 0.046471, Train CE:0.027337, Train KL:4.053070, Val MSE:0.042231, Val CE:0.024462, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+epoch: 18, beta = 0.010000, Train MSE: 0.040246, Train CE:0.022255, Train KL:4.026280, Val MSE:0.037435, Val CE:0.020018, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+epoch: 19, beta = 0.010000, Train MSE: 0.035564, Train CE:0.018355, Train KL:4.001863, Val MSE:0.033428, Val CE:0.016659, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 21/4000: 100%|██████████| 10/10 [00:00<00:00, 10.20it/s]
+epoch: 20, beta = 0.010000, Train MSE: 0.032023, Train CE:0.015323, Train KL:3.975580, Val MSE:0.030635, Val CE:0.014008, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 22/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 22/4000: 100%|██████████| 10/10 [00:00<00:00, 10.70it/s]
+epoch: 21, beta = 0.010000, Train MSE: 0.029129, Train CE:0.013011, Train KL:3.941919, Val MSE:0.027524, Val CE:0.012029, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+epoch: 22, beta = 0.010000, Train MSE: 0.026823, Train CE:0.011231, Train KL:3.903429, Val MSE:0.025573, Val CE:0.010473, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 161/4000:  40%|████      | 4/10 [00:00<00:00,  7.35it/s]
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+Epoch 161/4000: 100%|██████████| 10/10 [00:00<00:00, 16.42it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 164/4000:  30%|███       | 3/10 [00:00<00:01,  5.59it/s]
+Epoch 164/4000:  60%|██████    | 6/10 [00:00<00:00, 10.48it/s]
+Epoch 164/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.59it/s]
+Epoch 164/4000: 100%|██████████| 10/10 [00:01<00:00,  9.58it/s]
+epoch: 163, beta = 0.007000, Train MSE: 0.003067, Train CE:0.000151, Train KL:2.087937, Val MSE:0.003061, Val CE:0.000174, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 165/4000:  10%|█         | 1/10 [00:00<00:04,  2.02it/s]
+Epoch 165/4000:  40%|████      | 4/10 [00:00<00:00,  7.66it/s]
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+Epoch 165/4000: 100%|██████████| 10/10 [00:00<00:00, 16.40it/s]
+Epoch 165/4000: 100%|██████████| 10/10 [00:00<00:00, 10.31it/s]
+epoch: 164, beta = 0.007000, Train MSE: 0.003018, Train CE:0.000407, Train KL:2.089138, Val MSE:0.002897, Val CE:0.000135, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 166/4000: 100%|██████████| 10/10 [00:00<00:00, 15.18it/s]
+Epoch 166/4000: 100%|██████████| 10/10 [00:01<00:00,  9.57it/s]
+epoch: 165, beta = 0.007000, Train MSE: 0.002812, Train CE:0.000119, Train KL:2.152687, Val MSE:0.002882, Val CE:0.000116, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 167/4000:  70%|███████   | 7/10 [00:00<00:00, 12.10it/s]
+Epoch 167/4000: 100%|██████████| 10/10 [00:00<00:00, 15.41it/s]
+Epoch 167/4000: 100%|██████████| 10/10 [00:01<00:00,  9.83it/s]
+epoch: 166, beta = 0.007000, Train MSE: 0.002984, Train CE:0.000123, Train KL:2.108832, Val MSE:0.003210, Val CE:0.000129, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 168/4000:  80%|████████  | 8/10 [00:00<00:00, 13.78it/s]
+Epoch 168/4000: 100%|██████████| 10/10 [00:00<00:00, 10.30it/s]
+epoch: 167, beta = 0.007000, Train MSE: 0.003109, Train CE:0.000141, Train KL:2.070158, Val MSE:0.002945, Val CE:0.000130, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 169/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
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+Epoch 169/4000:  70%|███████   | 7/10 [00:00<00:00, 12.30it/s]
+Epoch 169/4000: 100%|██████████| 10/10 [00:00<00:00, 16.28it/s]
+Epoch 169/4000: 100%|██████████| 10/10 [00:00<00:00, 10.10it/s]
+epoch: 168, beta = 0.007000, Train MSE: 0.002927, Train CE:0.000214, Train KL:2.097092, Val MSE:0.002878, Val CE:0.000129, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 171/4000: 100%|██████████| 10/10 [00:00<00:00, 16.71it/s]
+Epoch 171/4000: 100%|██████████| 10/10 [00:00<00:00, 10.43it/s]
+epoch: 170, beta = 0.007000, Train MSE: 0.003023, Train CE:0.000199, Train KL:2.063179, Val MSE:0.002945, Val CE:0.000129, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 172/4000:  70%|███████   | 7/10 [00:00<00:00, 11.63it/s]
+Epoch 172/4000: 100%|██████████| 10/10 [00:00<00:00, 15.75it/s]
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+epoch: 171, beta = 0.007000, Train MSE: 0.002893, Train CE:0.000128, Train KL:2.080636, Val MSE:0.002927, Val CE:0.000145, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 173/4000:  70%|███████   | 7/10 [00:00<00:00, 12.37it/s]
+Epoch 173/4000: 100%|██████████| 10/10 [00:00<00:00, 15.91it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 175/4000:  70%|███████   | 7/10 [00:00<00:00, 10.93it/s]
+Epoch 175/4000: 100%|██████████| 10/10 [00:00<00:00, 14.23it/s]
+Epoch 175/4000: 100%|██████████| 10/10 [00:01<00:00,  8.99it/s]
+epoch: 174, beta = 0.007000, Train MSE: 0.003005, Train CE:0.000149, Train KL:2.042744, Val MSE:0.002931, Val CE:0.000159, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 176/4000:  30%|███       | 3/10 [00:00<00:01,  5.07it/s]
+Epoch 176/4000:  50%|█████     | 5/10 [00:00<00:00,  8.23it/s]
+Epoch 176/4000:  80%|████████  | 8/10 [00:00<00:00, 13.08it/s]
+Epoch 176/4000: 100%|██████████| 10/10 [00:01<00:00,  9.14it/s]
+epoch: 175, beta = 0.004900, Train MSE: 0.002904, Train CE:0.000158, Train KL:2.049786, Val MSE:0.002834, Val CE:0.000131, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 177/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
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+Epoch 177/4000:  70%|███████   | 7/10 [00:00<00:00, 12.37it/s]
+Epoch 177/4000: 100%|██████████| 10/10 [00:00<00:00, 16.28it/s]
+Epoch 177/4000: 100%|██████████| 10/10 [00:00<00:00, 10.07it/s]
+Learning rate updated: 0.00095
+epoch: 176, beta = 0.004900, Train MSE: 0.002718, Train CE:0.000153, Train KL:2.067798, Val MSE:0.002539, Val CE:0.000128, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 178/4000: 100%|██████████| 10/10 [00:00<00:00, 15.28it/s]
+Epoch 178/4000: 100%|██████████| 10/10 [00:01<00:00,  9.59it/s]
+epoch: 177, beta = 0.004900, Train MSE: 0.002430, Train CE:0.000125, Train KL:2.122418, Val MSE:0.002299, Val CE:0.000175, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 179/4000: 100%|██████████| 10/10 [00:01<00:00,  9.85it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 180/4000:  80%|████████  | 8/10 [00:00<00:00, 13.70it/s]
+Epoch 180/4000: 100%|██████████| 10/10 [00:00<00:00, 10.32it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 181/4000:  40%|████      | 4/10 [00:00<00:00,  7.50it/s]
+Epoch 181/4000:  70%|███████   | 7/10 [00:00<00:00, 12.52it/s]
+Epoch 181/4000: 100%|██████████| 10/10 [00:00<00:00, 16.21it/s]
+Epoch 181/4000: 100%|██████████| 10/10 [00:00<00:00, 10.11it/s]
+epoch: 180, beta = 0.004900, Train MSE: 0.002142, Train CE:0.000119, Train KL:2.160549, Val MSE:0.002195, Val CE:0.000112, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 182/4000:  80%|████████  | 8/10 [00:00<00:00, 13.07it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 183/4000:  10%|█         | 1/10 [00:00<00:04,  1.92it/s]
+Epoch 183/4000:  40%|████      | 4/10 [00:00<00:00,  7.53it/s]
+Epoch 183/4000:  70%|███████   | 7/10 [00:00<00:00, 12.41it/s]
+Epoch 183/4000: 100%|██████████| 10/10 [00:00<00:00, 16.52it/s]
+Epoch 183/4000: 100%|██████████| 10/10 [00:00<00:00, 10.25it/s]
+epoch: 182, beta = 0.004900, Train MSE: 0.002089, Train CE:0.000092, Train KL:2.217031, Val MSE:0.002146, Val CE:0.000093, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 184/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 184/4000:  40%|████      | 4/10 [00:00<00:00,  7.23it/s]
+Epoch 184/4000:  60%|██████    | 6/10 [00:00<00:00,  9.96it/s]
+Epoch 184/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.87it/s]
+Epoch 184/4000: 100%|██████████| 10/10 [00:01<00:00,  9.48it/s]
+epoch: 183, beta = 0.004900, Train MSE: 0.002201, Train CE:0.000096, Train KL:2.164433, Val MSE:0.002312, Val CE:0.000115, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 185/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 185/4000:  10%|█         | 1/10 [00:00<00:04,  1.93it/s]
+Epoch 185/4000:  40%|████      | 4/10 [00:00<00:00,  7.67it/s]
+Epoch 185/4000:  80%|████████  | 8/10 [00:00<00:00, 14.09it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 186/4000: 100%|██████████| 10/10 [00:01<00:00,  9.79it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 187/4000: 100%|██████████| 10/10 [00:00<00:00, 16.24it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 188/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 188/4000:  40%|████      | 4/10 [00:00<00:00,  7.07it/s]
+Epoch 188/4000:  70%|███████   | 7/10 [00:00<00:00, 11.98it/s]
+Epoch 188/4000: 100%|██████████| 10/10 [00:00<00:00, 16.09it/s]
+Epoch 188/4000: 100%|██████████| 10/10 [00:01<00:00,  9.75it/s]
+epoch: 187, beta = 0.004900, Train MSE: 0.002175, Train CE:0.000113, Train KL:2.117147, Val MSE:0.002116, Val CE:0.000282, Train ACC:1.000000, Val ACC:0.999777
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 189/4000:  10%|█         | 1/10 [00:00<00:04,  1.83it/s]
+Epoch 189/4000:  40%|████      | 4/10 [00:00<00:00,  7.21it/s]
+Epoch 189/4000:  70%|███████   | 7/10 [00:00<00:00, 11.30it/s]
+Epoch 189/4000: 100%|██████████| 10/10 [00:00<00:00, 14.53it/s]
+Epoch 189/4000: 100%|██████████| 10/10 [00:01<00:00,  9.27it/s]
+epoch: 188, beta = 0.004900, Train MSE: 0.002137, Train CE:0.000153, Train KL:2.118605, Val MSE:0.002316, Val CE:0.000106, Train ACC:0.999712, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 190/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 190/4000:  40%|████      | 4/10 [00:00<00:00,  7.24it/s]
+Epoch 190/4000:  70%|███████   | 7/10 [00:00<00:00, 12.07it/s]
+Epoch 190/4000: 100%|██████████| 10/10 [00:00<00:00, 15.70it/s]
+Epoch 190/4000: 100%|██████████| 10/10 [00:01<00:00,  9.83it/s]
+epoch: 189, beta = 0.004900, Train MSE: 0.002156, Train CE:0.000095, Train KL:2.172549, Val MSE:0.002034, Val CE:0.000088, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 191/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 191/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 191/4000:  40%|████      | 4/10 [00:00<00:00,  7.32it/s]
+Epoch 191/4000:  80%|████████  | 8/10 [00:00<00:00, 13.60it/s]
+Epoch 191/4000: 100%|██████████| 10/10 [00:00<00:00, 10.18it/s]
+epoch: 190, beta = 0.004900, Train MSE: 0.002079, Train CE:0.000089, Train KL:2.171001, Val MSE:0.002095, Val CE:0.000090, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 192/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 192/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 192/4000:  40%|████      | 4/10 [00:00<00:00,  7.27it/s]
+Epoch 192/4000:  80%|████████  | 8/10 [00:00<00:00, 13.39it/s]
+Epoch 192/4000: 100%|██████████| 10/10 [00:00<00:00, 10.08it/s]
+epoch: 191, beta = 0.004900, Train MSE: 0.002169, Train CE:0.000097, Train KL:2.121967, Val MSE:0.002169, Val CE:0.000098, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 193/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 193/4000:  10%|█         | 1/10 [00:00<00:05,  1.80it/s]
+Epoch 193/4000:  40%|████      | 4/10 [00:00<00:00,  7.17it/s]
+Epoch 193/4000:  70%|███████   | 7/10 [00:00<00:00, 11.60it/s]
+Epoch 193/4000: 100%|██████████| 10/10 [00:00<00:00, 15.38it/s]
+Epoch 193/4000: 100%|██████████| 10/10 [00:01<00:00,  9.41it/s]
+epoch: 192, beta = 0.004900, Train MSE: 0.002139, Train CE:0.000100, Train KL:2.113965, Val MSE:0.002115, Val CE:0.000103, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 194/4000:  10%|█         | 1/10 [00:00<00:05,  1.57it/s]
+Epoch 194/4000:  40%|████      | 4/10 [00:00<00:00,  6.53it/s]
+Epoch 194/4000:  80%|████████  | 8/10 [00:00<00:00, 12.54it/s]
+Epoch 194/4000: 100%|██████████| 10/10 [00:01<00:00,  9.28it/s]
+epoch: 193, beta = 0.004900, Train MSE: 0.002104, Train CE:0.000101, Train KL:2.112089, Val MSE:0.002170, Val CE:0.000147, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 195/4000:  10%|█         | 1/10 [00:00<00:04,  1.95it/s]
+Epoch 195/4000:  40%|████      | 4/10 [00:00<00:00,  7.65it/s]
+Epoch 195/4000:  70%|███████   | 7/10 [00:00<00:00, 12.65it/s]
+Epoch 195/4000: 100%|██████████| 10/10 [00:00<00:00, 16.48it/s]
+Epoch 195/4000: 100%|██████████| 10/10 [00:00<00:00, 10.33it/s]
+epoch: 194, beta = 0.004900, Train MSE: 0.002136, Train CE:0.000112, Train KL:2.098689, Val MSE:0.002149, Val CE:0.000112, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 196/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 196/4000:  10%|█         | 1/10 [00:00<00:05,  1.79it/s]
+Epoch 196/4000:  40%|████      | 4/10 [00:00<00:00,  6.86it/s]
+Epoch 196/4000:  70%|███████   | 7/10 [00:00<00:00, 11.60it/s]
+Epoch 196/4000: 100%|██████████| 10/10 [00:00<00:00, 15.29it/s]
+Epoch 196/4000: 100%|██████████| 10/10 [00:01<00:00,  9.58it/s]
+epoch: 195, beta = 0.004900, Train MSE: 0.002082, Train CE:0.000130, Train KL:2.101996, Val MSE:0.002014, Val CE:0.000102, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 197/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 197/4000:  10%|█         | 1/10 [00:00<00:05,  1.52it/s]
+Epoch 197/4000:  40%|████      | 4/10 [00:00<00:00,  6.50it/s]
+Epoch 197/4000:  70%|███████   | 7/10 [00:00<00:00, 11.09it/s]
+Epoch 197/4000: 100%|██████████| 10/10 [00:01<00:00, 14.35it/s]
+Epoch 197/4000: 100%|██████████| 10/10 [00:01<00:00,  8.71it/s]
+epoch: 196, beta = 0.004900, Train MSE: 0.002035, Train CE:0.000099, Train KL:2.114712, Val MSE:0.002020, Val CE:0.000095, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 198/4000:  40%|████      | 4/10 [00:00<00:00,  6.86it/s]
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+Epoch 198/4000: 100%|██████████| 10/10 [00:00<00:00, 14.96it/s]
+Epoch 198/4000: 100%|██████████| 10/10 [00:01<00:00,  9.33it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 199/4000:  10%|█         | 1/10 [00:00<00:05,  1.79it/s]
+Epoch 199/4000:  40%|████      | 4/10 [00:00<00:00,  6.93it/s]
+Epoch 199/4000:  70%|███████   | 7/10 [00:00<00:00, 11.23it/s]
+Epoch 199/4000: 100%|██████████| 10/10 [00:00<00:00, 14.71it/s]
+Epoch 199/4000: 100%|██████████| 10/10 [00:01<00:00,  9.39it/s]
+epoch: 198, beta = 0.004900, Train MSE: 0.002079, Train CE:0.000100, Train KL:2.089842, Val MSE:0.002112, Val CE:0.000102, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 200/4000:  40%|████      | 4/10 [00:00<00:00,  6.04it/s]
+Epoch 200/4000:  70%|███████   | 7/10 [00:00<00:00, 10.36it/s]
+Epoch 200/4000: 100%|██████████| 10/10 [00:01<00:00, 13.72it/s]
+Epoch 200/4000: 100%|██████████| 10/10 [00:01<00:00,  8.46it/s]
+epoch: 199, beta = 0.003430, Train MSE: 0.002078, Train CE:0.000105, Train KL:2.083270, Val MSE:0.002041, Val CE:0.000103, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 201/4000:  40%|████      | 4/10 [00:00<00:00,  7.67it/s]
+Epoch 201/4000:  70%|███████   | 7/10 [00:00<00:00, 12.52it/s]
+Epoch 201/4000: 100%|██████████| 10/10 [00:00<00:00, 16.31it/s]
+Epoch 201/4000: 100%|██████████| 10/10 [00:00<00:00, 10.32it/s]
+Learning rate updated: 0.0009025
+epoch: 200, beta = 0.003430, Train MSE: 0.001995, Train CE:0.000115, Train KL:2.104681, Val MSE:0.001800, Val CE:0.000097, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 202/4000:  70%|███████   | 7/10 [00:00<00:00, 10.94it/s]
+Epoch 202/4000: 100%|██████████| 10/10 [00:00<00:00, 14.65it/s]
+Epoch 202/4000: 100%|██████████| 10/10 [00:01<00:00,  9.12it/s]
+epoch: 201, beta = 0.003430, Train MSE: 0.001752, Train CE:0.000092, Train KL:2.160013, Val MSE:0.001680, Val CE:0.000092, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 203/4000:  10%|█         | 1/10 [00:00<00:05,  1.79it/s]
+Epoch 203/4000:  40%|████      | 4/10 [00:00<00:00,  7.15it/s]
+Epoch 203/4000:  80%|████████  | 8/10 [00:00<00:00, 13.29it/s]
+Epoch 203/4000: 100%|██████████| 10/10 [00:01<00:00,  9.93it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 204/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 204/4000:  40%|████      | 4/10 [00:00<00:00,  7.16it/s]
+Epoch 204/4000:  70%|███████   | 7/10 [00:00<00:00, 12.05it/s]
+Epoch 204/4000: 100%|██████████| 10/10 [00:00<00:00, 15.68it/s]
+Epoch 204/4000: 100%|██████████| 10/10 [00:01<00:00,  9.72it/s]
+epoch: 203, beta = 0.003430, Train MSE: 0.001643, Train CE:0.000097, Train KL:2.178294, Val MSE:0.001579, Val CE:0.000106, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 205/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
+Epoch 205/4000:  40%|████      | 4/10 [00:00<00:00,  7.25it/s]
+Epoch 205/4000:  80%|████████  | 8/10 [00:00<00:00, 13.30it/s]
+Epoch 205/4000: 100%|██████████| 10/10 [00:01<00:00,  9.97it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 206/4000:  70%|███████   | 7/10 [00:00<00:00, 12.15it/s]
+Epoch 206/4000: 100%|██████████| 10/10 [00:00<00:00, 16.01it/s]
+Epoch 206/4000: 100%|██████████| 10/10 [00:01<00:00,  9.88it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 207/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
+Epoch 207/4000:  40%|████      | 4/10 [00:00<00:00,  7.32it/s]
+Epoch 207/4000:  70%|███████   | 7/10 [00:00<00:00, 12.27it/s]
+Epoch 207/4000: 100%|██████████| 10/10 [00:00<00:00, 16.30it/s]
+Epoch 207/4000: 100%|██████████| 10/10 [00:01<00:00,  9.84it/s]
+epoch: 206, beta = 0.003430, Train MSE: 0.001574, Train CE:0.000091, Train KL:2.181212, Val MSE:0.001569, Val CE:0.000089, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 208/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 208/4000:  10%|█         | 1/10 [00:00<00:04,  1.99it/s]
+Epoch 208/4000:  40%|████      | 4/10 [00:00<00:00,  7.73it/s]
+Epoch 208/4000:  80%|████████  | 8/10 [00:00<00:00, 13.92it/s]
+Epoch 208/4000: 100%|██████████| 10/10 [00:00<00:00, 10.48it/s]
+epoch: 207, beta = 0.003430, Train MSE: 0.001548, Train CE:0.000104, Train KL:2.189919, Val MSE:0.001507, Val CE:0.000082, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 209/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 209/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 209/4000:  40%|████      | 4/10 [00:00<00:00,  7.01it/s]
+Epoch 209/4000:  70%|███████   | 7/10 [00:00<00:00, 11.48it/s]
+Epoch 209/4000: 100%|██████████| 10/10 [00:00<00:00, 15.42it/s]
+Epoch 209/4000: 100%|██████████| 10/10 [00:01<00:00,  9.65it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 210/4000:  30%|███       | 3/10 [00:00<00:01,  5.58it/s]
+Epoch 210/4000:  60%|██████    | 6/10 [00:00<00:00, 10.51it/s]
+Epoch 210/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.88it/s]
+Epoch 210/4000: 100%|██████████| 10/10 [00:01<00:00,  9.61it/s]
+epoch: 209, beta = 0.003430, Train MSE: 0.001562, Train CE:0.000086, Train KL:2.179853, Val MSE:0.001589, Val CE:0.000082, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 211/4000:  80%|████████  | 8/10 [00:00<00:00, 14.15it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 212/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 212/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
+Epoch 212/4000:  40%|████      | 4/10 [00:00<00:00,  7.42it/s]
+Epoch 212/4000:  70%|███████   | 7/10 [00:00<00:00, 12.40it/s]
+Epoch 212/4000: 100%|██████████| 10/10 [00:00<00:00, 16.58it/s]
+Epoch 212/4000: 100%|██████████| 10/10 [00:00<00:00, 10.13it/s]
+epoch: 211, beta = 0.003430, Train MSE: 0.001525, Train CE:0.000080, Train KL:2.185409, Val MSE:0.001522, Val CE:0.000086, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 213/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 213/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
+Epoch 213/4000:  40%|████      | 4/10 [00:00<00:00,  7.19it/s]
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+Epoch 213/4000: 100%|██████████| 10/10 [00:00<00:00, 15.43it/s]
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+epoch: 212, beta = 0.003430, Train MSE: 0.001513, Train CE:0.000088, Train KL:2.185309, Val MSE:0.001518, Val CE:0.000081, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 214/4000: 100%|██████████| 10/10 [00:01<00:00,  9.80it/s]
+epoch: 213, beta = 0.003430, Train MSE: 0.001526, Train CE:0.000134, Train KL:2.191114, Val MSE:0.001472, Val CE:0.000072, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 215/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 215/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
+Epoch 215/4000:  40%|████      | 4/10 [00:00<00:00,  7.43it/s]
+Epoch 215/4000:  70%|███████   | 7/10 [00:00<00:00, 12.39it/s]
+Epoch 215/4000: 100%|██████████| 10/10 [00:00<00:00, 16.33it/s]
+Epoch 215/4000: 100%|██████████| 10/10 [00:00<00:00, 10.12it/s]
+epoch: 214, beta = 0.003430, Train MSE: 0.001526, Train CE:0.000071, Train KL:2.211004, Val MSE:0.001501, Val CE:0.000070, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 216/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 216/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 216/4000:  40%|████      | 4/10 [00:00<00:00,  7.17it/s]
+Epoch 216/4000:  80%|████████  | 8/10 [00:00<00:00, 13.31it/s]
+Epoch 216/4000: 100%|██████████| 10/10 [00:01<00:00,  9.94it/s]
+epoch: 215, beta = 0.003430, Train MSE: 0.001557, Train CE:0.000073, Train KL:2.181302, Val MSE:0.001561, Val CE:0.000074, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 217/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 217/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 217/4000:  40%|████      | 4/10 [00:00<00:00,  7.37it/s]
+Epoch 217/4000:  80%|████████  | 8/10 [00:00<00:00, 13.73it/s]
+Epoch 217/4000: 100%|██████████| 10/10 [00:00<00:00, 10.15it/s]
+epoch: 216, beta = 0.003430, Train MSE: 0.001535, Train CE:0.000075, Train KL:2.167801, Val MSE:0.001527, Val CE:0.000078, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 218/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 218/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 218/4000:  40%|████      | 4/10 [00:00<00:00,  7.37it/s]
+Epoch 218/4000:  70%|███████   | 7/10 [00:00<00:00, 12.23it/s]
+Epoch 218/4000: 100%|██████████| 10/10 [00:00<00:00, 16.27it/s]
+Epoch 218/4000: 100%|██████████| 10/10 [00:00<00:00, 10.08it/s]
+epoch: 217, beta = 0.003430, Train MSE: 0.001509, Train CE:0.000076, Train KL:2.168943, Val MSE:0.001533, Val CE:0.000081, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 219/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 219/4000:  10%|█         | 1/10 [00:00<00:04,  2.06it/s]
+Epoch 219/4000:  40%|████      | 4/10 [00:00<00:00,  7.55it/s]
+Epoch 219/4000:  70%|███████   | 7/10 [00:00<00:00, 12.12it/s]
+Epoch 219/4000: 100%|██████████| 10/10 [00:00<00:00, 15.56it/s]
+Epoch 219/4000: 100%|██████████| 10/10 [00:00<00:00, 10.04it/s]
+epoch: 218, beta = 0.003430, Train MSE: 0.001503, Train CE:0.000082, Train KL:2.161920, Val MSE:0.001523, Val CE:0.000081, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 220/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 220/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 220/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 220/4000:  70%|███████   | 7/10 [00:00<00:00, 11.60it/s]
+Epoch 220/4000: 100%|██████████| 10/10 [00:00<00:00, 15.46it/s]
+Epoch 220/4000: 100%|██████████| 10/10 [00:01<00:00,  9.56it/s]
+epoch: 219, beta = 0.003430, Train MSE: 0.001500, Train CE:0.000079, Train KL:2.158648, Val MSE:0.001500, Val CE:0.000080, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 221/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 221/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 221/4000:  40%|████      | 4/10 [00:00<00:00,  6.73it/s]
+Epoch 221/4000:  70%|███████   | 7/10 [00:00<00:00, 11.42it/s]
+Epoch 221/4000: 100%|██████████| 10/10 [00:00<00:00, 15.49it/s]
+Epoch 221/4000: 100%|██████████| 10/10 [00:01<00:00,  9.44it/s]
+epoch: 220, beta = 0.003430, Train MSE: 0.001502, Train CE:0.000083, Train KL:2.154029, Val MSE:0.001512, Val CE:0.000088, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 222/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 222/4000:  10%|█         | 1/10 [00:00<00:04,  2.07it/s]
+Epoch 222/4000:  40%|████      | 4/10 [00:00<00:00,  8.02it/s]
+Epoch 222/4000:  80%|████████  | 8/10 [00:00<00:00, 14.75it/s]
+Epoch 222/4000: 100%|██████████| 10/10 [00:00<00:00, 10.97it/s]
+epoch: 221, beta = 0.003430, Train MSE: 0.001494, Train CE:0.000084, Train KL:2.151480, Val MSE:0.001466, Val CE:0.000080, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 223/4000:  10%|█         | 1/10 [00:00<00:04,  1.83it/s]
+Epoch 223/4000:  40%|████      | 4/10 [00:00<00:00,  7.12it/s]
+Epoch 223/4000:  80%|████████  | 8/10 [00:00<00:00, 13.37it/s]
+Epoch 223/4000: 100%|██████████| 10/10 [00:01<00:00,  9.94it/s]
+epoch: 222, beta = 0.003430, Train MSE: 0.001481, Train CE:0.000082, Train KL:2.153514, Val MSE:0.001474, Val CE:0.000080, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 224/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 224/4000:  10%|█         | 1/10 [00:00<00:04,  1.93it/s]
+Epoch 224/4000:  40%|████      | 4/10 [00:00<00:00,  7.55it/s]
+Epoch 224/4000:  80%|████████  | 8/10 [00:00<00:00, 13.82it/s]
+Epoch 224/4000: 100%|██████████| 10/10 [00:00<00:00, 10.28it/s]
+epoch: 223, beta = 0.003430, Train MSE: 0.001470, Train CE:0.000095, Train KL:2.151818, Val MSE:0.001433, Val CE:0.000073, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 225/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 225/4000:  10%|█         | 1/10 [00:00<00:04,  1.87it/s]
+Epoch 225/4000:  40%|████      | 4/10 [00:00<00:00,  7.53it/s]
+Epoch 225/4000:  80%|████████  | 8/10 [00:00<00:00, 13.99it/s]
+Epoch 225/4000: 100%|██████████| 10/10 [00:00<00:00, 10.38it/s]
+epoch: 224, beta = 0.002401, Train MSE: 0.001454, Train CE:0.000073, Train KL:2.160777, Val MSE:0.001460, Val CE:0.000071, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 226/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 226/4000:  10%|█         | 1/10 [00:00<00:04,  1.89it/s]
+Epoch 226/4000:  40%|████      | 4/10 [00:00<00:00,  7.41it/s]
+Epoch 226/4000:  70%|███████   | 7/10 [00:00<00:00, 12.40it/s]
+Epoch 226/4000: 100%|██████████| 10/10 [00:00<00:00, 16.26it/s]
+Epoch 226/4000: 100%|██████████| 10/10 [00:00<00:00, 10.12it/s]
+Learning rate updated: 0.000857375
+epoch: 225, beta = 0.002401, Train MSE: 0.001433, Train CE:0.000072, Train KL:2.158935, Val MSE:0.001380, Val CE:0.000073, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 227/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 227/4000:  40%|████      | 4/10 [00:00<00:00,  7.21it/s]
+Epoch 227/4000:  70%|███████   | 7/10 [00:00<00:00, 11.84it/s]
+Epoch 227/4000: 100%|██████████| 10/10 [00:00<00:00, 15.70it/s]
+Epoch 227/4000: 100%|██████████| 10/10 [00:01<00:00,  9.60it/s]
+epoch: 226, beta = 0.002401, Train MSE: 0.001307, Train CE:0.000076, Train KL:2.195892, Val MSE:0.001267, Val CE:0.000071, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 228/4000:  10%|█         | 1/10 [00:00<00:04,  1.99it/s]
+Epoch 228/4000:  40%|████      | 4/10 [00:00<00:00,  7.77it/s]
+Epoch 228/4000:  80%|████████  | 8/10 [00:00<00:00, 14.28it/s]
+Epoch 228/4000: 100%|██████████| 10/10 [00:00<00:00, 10.64it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 229/4000:  10%|█         | 1/10 [00:00<00:04,  1.90it/s]
+Epoch 229/4000:  40%|████      | 4/10 [00:00<00:00,  7.33it/s]
+Epoch 229/4000:  70%|███████   | 7/10 [00:00<00:00, 12.26it/s]
+Epoch 229/4000: 100%|██████████| 10/10 [00:00<00:00, 15.99it/s]
+Epoch 229/4000: 100%|██████████| 10/10 [00:00<00:00, 10.04it/s]
+epoch: 228, beta = 0.002401, Train MSE: 0.001187, Train CE:0.000071, Train KL:2.238361, Val MSE:0.001177, Val CE:0.000070, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 230/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
+Epoch 230/4000:  40%|████      | 4/10 [00:00<00:00,  7.51it/s]
+Epoch 230/4000:  80%|████████  | 8/10 [00:00<00:00, 13.91it/s]
+Epoch 230/4000: 100%|██████████| 10/10 [00:00<00:00, 10.37it/s]
+epoch: 229, beta = 0.002401, Train MSE: 0.001173, Train CE:0.000071, Train KL:2.240205, Val MSE:0.001154, Val CE:0.000068, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 231/4000:  40%|████      | 4/10 [00:00<00:00,  7.73it/s]
+Epoch 231/4000:  70%|███████   | 7/10 [00:00<00:00, 12.83it/s]
+Epoch 231/4000: 100%|██████████| 10/10 [00:00<00:00, 16.69it/s]
+Epoch 231/4000: 100%|██████████| 10/10 [00:00<00:00, 10.40it/s]
+epoch: 230, beta = 0.002401, Train MSE: 0.001137, Train CE:0.000074, Train KL:2.247018, Val MSE:0.001127, Val CE:0.000070, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 232/4000:  10%|█         | 1/10 [00:00<00:04,  1.97it/s]
+Epoch 232/4000:  40%|████      | 4/10 [00:00<00:00,  7.81it/s]
+Epoch 232/4000:  80%|████████  | 8/10 [00:00<00:00, 14.09it/s]
+Epoch 232/4000: 100%|██████████| 10/10 [00:00<00:00, 10.58it/s]
+epoch: 231, beta = 0.002401, Train MSE: 0.001131, Train CE:0.000074, Train KL:2.249581, Val MSE:0.001109, Val CE:0.000165, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 233/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 233/4000:  10%|█         | 1/10 [00:00<00:04,  1.91it/s]
+Epoch 233/4000:  40%|████      | 4/10 [00:00<00:00,  7.45it/s]
+Epoch 233/4000:  70%|███████   | 7/10 [00:00<00:00, 12.34it/s]
+Epoch 233/4000: 100%|██████████| 10/10 [00:00<00:00, 16.50it/s]
+Epoch 233/4000: 100%|██████████| 10/10 [00:00<00:00, 10.20it/s]
+epoch: 232, beta = 0.002401, Train MSE: 0.001116, Train CE:0.000067, Train KL:2.250783, Val MSE:0.001128, Val CE:0.000067, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 234/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 234/4000:  10%|█         | 1/10 [00:00<00:04,  2.01it/s]
+Epoch 234/4000:  40%|████      | 4/10 [00:00<00:00,  7.79it/s]
+Epoch 234/4000:  70%|███████   | 7/10 [00:00<00:00, 12.90it/s]
+Epoch 234/4000: 100%|██████████| 10/10 [00:00<00:00, 16.97it/s]
+Epoch 234/4000: 100%|██████████| 10/10 [00:00<00:00, 10.65it/s]
+epoch: 233, beta = 0.002401, Train MSE: 0.001127, Train CE:0.000068, Train KL:2.244665, Val MSE:0.001130, Val CE:0.000068, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 235/4000:  80%|████████  | 8/10 [00:00<00:00, 14.56it/s]
+Epoch 235/4000: 100%|██████████| 10/10 [00:00<00:00, 10.71it/s]
+epoch: 234, beta = 0.002401, Train MSE: 0.001129, Train CE:0.000067, Train KL:2.240277, Val MSE:0.001130, Val CE:0.000066, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 236/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 236/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 236/4000:  40%|████      | 4/10 [00:00<00:00,  7.39it/s]
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+Epoch 236/4000: 100%|██████████| 10/10 [00:00<00:00, 15.82it/s]
+Epoch 236/4000: 100%|██████████| 10/10 [00:01<00:00,  9.62it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 237/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 237/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 237/4000:  40%|████      | 4/10 [00:00<00:00,  7.51it/s]
+Epoch 237/4000:  80%|████████  | 8/10 [00:00<00:00, 13.80it/s]
+Epoch 237/4000: 100%|██████████| 10/10 [00:00<00:00, 10.28it/s]
+epoch: 236, beta = 0.002401, Train MSE: 0.001066, Train CE:0.000058, Train KL:2.283874, Val MSE:0.001072, Val CE:0.000057, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 238/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 238/4000:  40%|████      | 4/10 [00:00<00:00,  7.28it/s]
+Epoch 238/4000:  70%|███████   | 7/10 [00:00<00:00, 12.16it/s]
+Epoch 238/4000: 100%|██████████| 10/10 [00:00<00:00, 16.11it/s]
+Epoch 238/4000: 100%|██████████| 10/10 [00:01<00:00,  9.75it/s]
+epoch: 237, beta = 0.002401, Train MSE: 0.001093, Train CE:0.000059, Train KL:2.261688, Val MSE:0.001124, Val CE:0.000061, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 239/4000:  70%|███████   | 7/10 [00:00<00:00, 11.45it/s]
+Epoch 239/4000: 100%|██████████| 10/10 [00:00<00:00, 14.60it/s]
+Epoch 239/4000: 100%|██████████| 10/10 [00:01<00:00,  9.00it/s]
+epoch: 238, beta = 0.002401, Train MSE: 0.001119, Train CE:0.000060, Train KL:2.239133, Val MSE:0.001117, Val CE:0.000060, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 240/4000: 100%|██████████| 10/10 [00:00<00:00, 15.68it/s]
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+epoch: 239, beta = 0.002401, Train MSE: 0.001118, Train CE:0.000061, Train KL:2.237829, Val MSE:0.001110, Val CE:0.000061, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 241/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 241/4000:  10%|█         | 1/10 [00:00<00:04,  1.90it/s]
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+epoch: 240, beta = 0.002401, Train MSE: 0.001103, Train CE:0.000061, Train KL:2.237034, Val MSE:0.001104, Val CE:0.000069, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 242/4000:  10%|█         | 1/10 [00:00<00:04,  1.97it/s]
+Epoch 242/4000:  40%|████      | 4/10 [00:00<00:00,  7.62it/s]
+Epoch 242/4000:  80%|████████  | 8/10 [00:00<00:00, 13.90it/s]
+Epoch 242/4000: 100%|██████████| 10/10 [00:00<00:00, 10.27it/s]
+epoch: 241, beta = 0.002401, Train MSE: 0.001104, Train CE:0.000062, Train KL:2.232202, Val MSE:0.001121, Val CE:0.000063, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 243/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 243/4000:  10%|█         | 1/10 [00:00<00:04,  1.80it/s]
+Epoch 243/4000:  40%|████      | 4/10 [00:00<00:00,  7.26it/s]
+Epoch 243/4000:  80%|████████  | 8/10 [00:00<00:00, 13.43it/s]
+Epoch 243/4000: 100%|██████████| 10/10 [00:01<00:00,  9.99it/s]
+epoch: 242, beta = 0.002401, Train MSE: 0.001094, Train CE:0.000139, Train KL:2.234791, Val MSE:0.001069, Val CE:0.000055, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 244/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 244/4000:  10%|█         | 1/10 [00:00<00:04,  1.95it/s]
+Epoch 244/4000:  40%|████      | 4/10 [00:00<00:00,  7.57it/s]
+Epoch 244/4000:  70%|███████   | 7/10 [00:00<00:00, 12.57it/s]
+Epoch 244/4000: 100%|██████████| 10/10 [00:00<00:00, 15.84it/s]
+Epoch 244/4000: 100%|██████████| 10/10 [00:00<00:00, 10.11it/s]
+epoch: 243, beta = 0.002401, Train MSE: 0.001030, Train CE:0.000054, Train KL:2.281414, Val MSE:0.001038, Val CE:0.000053, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 245/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 245/4000:  10%|█         | 1/10 [00:00<00:04,  1.83it/s]
+Epoch 245/4000:  40%|████      | 4/10 [00:00<00:00,  7.33it/s]
+Epoch 245/4000:  70%|███████   | 7/10 [00:00<00:00, 12.13it/s]
+Epoch 245/4000: 100%|██████████| 10/10 [00:00<00:00, 15.82it/s]
+Epoch 245/4000: 100%|██████████| 10/10 [00:01<00:00,  9.93it/s]
+epoch: 244, beta = 0.002401, Train MSE: 0.001068, Train CE:0.000053, Train KL:2.267131, Val MSE:0.001087, Val CE:0.000054, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 246/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 246/4000:  10%|█         | 1/10 [00:00<00:04,  1.98it/s]
+Epoch 246/4000:  40%|████      | 4/10 [00:00<00:00,  7.83it/s]
+Epoch 246/4000:  80%|████████  | 8/10 [00:00<00:00, 14.31it/s]
+Epoch 246/4000: 100%|██████████| 10/10 [00:00<00:00, 10.79it/s]
+epoch: 245, beta = 0.002401, Train MSE: 0.001104, Train CE:0.000055, Train KL:2.234146, Val MSE:0.001097, Val CE:0.000055, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 247/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 247/4000:  10%|█         | 1/10 [00:00<00:04,  1.89it/s]
+Epoch 247/4000:  40%|████      | 4/10 [00:00<00:00,  7.21it/s]
+Epoch 247/4000:  70%|███████   | 7/10 [00:00<00:00, 12.15it/s]
+Epoch 247/4000: 100%|██████████| 10/10 [00:00<00:00, 16.28it/s]
+Epoch 247/4000: 100%|██████████| 10/10 [00:00<00:00, 10.07it/s]
+epoch: 246, beta = 0.002401, Train MSE: 0.001102, Train CE:0.000056, Train KL:2.227861, Val MSE:0.001118, Val CE:0.000056, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 248/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 248/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 248/4000:  40%|████      | 4/10 [00:00<00:00,  7.09it/s]
+Epoch 248/4000:  70%|███████   | 7/10 [00:00<00:00, 11.80it/s]
+Epoch 248/4000: 100%|██████████| 10/10 [00:00<00:00, 15.72it/s]
+Epoch 248/4000: 100%|██████████| 10/10 [00:01<00:00,  9.77it/s]
+epoch: 247, beta = 0.002401, Train MSE: 0.001088, Train CE:0.000058, Train KL:2.228949, Val MSE:0.001054, Val CE:0.000056, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 249/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 249/4000:  10%|█         | 1/10 [00:00<00:04,  1.94it/s]
+Epoch 249/4000:  40%|████      | 4/10 [00:00<00:00,  7.78it/s]
+Epoch 249/4000:  80%|████████  | 8/10 [00:00<00:00, 14.28it/s]
+Epoch 249/4000: 100%|██████████| 10/10 [00:00<00:00, 10.62it/s]
+epoch: 248, beta = 0.002401, Train MSE: 0.001082, Train CE:0.000153, Train KL:2.230489, Val MSE:0.001095, Val CE:0.000055, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 250/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 250/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 250/4000:  40%|████      | 4/10 [00:00<00:00,  7.36it/s]
+Epoch 250/4000:  80%|████████  | 8/10 [00:00<00:00, 13.62it/s]
+Epoch 250/4000: 100%|██████████| 10/10 [00:00<00:00, 10.15it/s]
+epoch: 249, beta = 0.002401, Train MSE: 0.001045, Train CE:0.000055, Train KL:2.291452, Val MSE:0.001030, Val CE:0.000056, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 251/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 251/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 251/4000:  40%|████      | 4/10 [00:00<00:00,  7.23it/s]
+Epoch 251/4000:  70%|███████   | 7/10 [00:00<00:00, 11.93it/s]
+Epoch 251/4000: 100%|██████████| 10/10 [00:00<00:00, 15.35it/s]
+Epoch 251/4000: 100%|██████████| 10/10 [00:01<00:00,  9.64it/s]
+epoch: 250, beta = 0.002401, Train MSE: 0.001031, Train CE:0.000057, Train KL:2.289659, Val MSE:0.001051, Val CE:0.000057, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 252/4000:  10%|█         | 1/10 [00:00<00:05,  1.63it/s]
+Epoch 252/4000:  40%|████      | 4/10 [00:00<00:00,  6.74it/s]
+Epoch 252/4000:  70%|███████   | 7/10 [00:00<00:00, 11.49it/s]
+Epoch 252/4000: 100%|██████████| 10/10 [00:00<00:00, 14.98it/s]
+Epoch 252/4000: 100%|██████████| 10/10 [00:01<00:00,  9.29it/s]
+epoch: 251, beta = 0.002401, Train MSE: 0.001061, Train CE:0.000058, Train KL:2.248516, Val MSE:0.001113, Val CE:0.000058, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 253/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 253/4000:  10%|█         | 1/10 [00:00<00:06,  1.37it/s]
+Epoch 253/4000:  40%|████      | 4/10 [00:00<00:01,  5.87it/s]
+Epoch 253/4000:  70%|███████   | 7/10 [00:00<00:00, 10.29it/s]
+Epoch 253/4000: 100%|██████████| 10/10 [00:01<00:00,  8.55it/s]
+epoch: 252, beta = 0.002401, Train MSE: 0.001125, Train CE:0.000059, Train KL:2.211334, Val MSE:0.001106, Val CE:0.000059, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 254/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 254/4000:  10%|█         | 1/10 [00:00<00:04,  1.94it/s]
+Epoch 254/4000:  40%|████      | 4/10 [00:00<00:00,  7.41it/s]
+Epoch 254/4000:  80%|████████  | 8/10 [00:00<00:00, 13.62it/s]
+Epoch 254/4000: 100%|██████████| 10/10 [00:00<00:00, 10.25it/s]
+epoch: 253, beta = 0.001681, Train MSE: 0.001099, Train CE:0.000058, Train KL:2.211826, Val MSE:0.001076, Val CE:0.000058, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 255/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 255/4000:  10%|█         | 1/10 [00:00<00:04,  1.92it/s]
+Epoch 255/4000:  40%|████      | 4/10 [00:00<00:00,  7.66it/s]
+Epoch 255/4000:  80%|████████  | 8/10 [00:00<00:00, 14.07it/s]
+Epoch 255/4000: 100%|██████████| 10/10 [00:00<00:00, 10.51it/s]
+Learning rate updated: 0.0008145062499999999
+epoch: 254, beta = 0.001681, Train MSE: 0.001052, Train CE:0.000057, Train KL:2.230315, Val MSE:0.001010, Val CE:0.000056, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 256/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 256/4000:  40%|████      | 4/10 [00:00<00:00,  7.09it/s]
+Epoch 256/4000:  70%|███████   | 7/10 [00:00<00:00, 11.83it/s]
+Epoch 256/4000: 100%|██████████| 10/10 [00:00<00:00, 15.26it/s]
+Epoch 256/4000: 100%|██████████| 10/10 [00:01<00:00,  9.43it/s]
+epoch: 255, beta = 0.001681, Train MSE: 0.000957, Train CE:0.000057, Train KL:2.268482, Val MSE:0.000928, Val CE:0.000054, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 257/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 257/4000:  30%|███       | 3/10 [00:00<00:01,  5.60it/s]
+Epoch 257/4000:  60%|██████    | 6/10 [00:00<00:00, 10.69it/s]
+Epoch 257/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.94it/s]
+Epoch 257/4000: 100%|██████████| 10/10 [00:01<00:00,  9.31it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 258/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 258/4000:  40%|████      | 4/10 [00:00<00:00,  7.04it/s]
+Epoch 258/4000:  80%|████████  | 8/10 [00:00<00:00, 13.20it/s]
+Epoch 258/4000: 100%|██████████| 10/10 [00:01<00:00,  9.84it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 259/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 259/4000:  40%|████      | 4/10 [00:00<00:00,  7.04it/s]
+Epoch 259/4000:  70%|███████   | 7/10 [00:00<00:00, 11.08it/s]
+Epoch 259/4000: 100%|██████████| 10/10 [00:00<00:00, 14.73it/s]
+Epoch 259/4000: 100%|██████████| 10/10 [00:01<00:00,  9.34it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 260/4000:  30%|███       | 3/10 [00:00<00:01,  5.56it/s]
+Epoch 260/4000:  60%|██████    | 6/10 [00:00<00:00, 10.48it/s]
+Epoch 260/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.21it/s]
+Epoch 260/4000: 100%|██████████| 10/10 [00:01<00:00,  9.42it/s]
+epoch: 259, beta = 0.001681, Train MSE: 0.000844, Train CE:0.000053, Train KL:2.315535, Val MSE:0.000857, Val CE:0.000054, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 261/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 261/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 261/4000:  40%|████      | 4/10 [00:00<00:00,  7.29it/s]
+Epoch 261/4000:  70%|███████   | 7/10 [00:00<00:00, 12.14it/s]
+Epoch 261/4000: 100%|██████████| 10/10 [00:00<00:00, 15.67it/s]
+Epoch 261/4000: 100%|██████████| 10/10 [00:01<00:00,  9.80it/s]
+epoch: 260, beta = 0.001681, Train MSE: 0.000834, Train CE:0.000055, Train KL:2.313111, Val MSE:0.000831, Val CE:0.000054, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 262/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 262/4000:  10%|█         | 1/10 [00:00<00:05,  1.79it/s]
+Epoch 262/4000:  40%|████      | 4/10 [00:00<00:00,  7.04it/s]
+Epoch 262/4000:  70%|███████   | 7/10 [00:00<00:00, 11.85it/s]
+Epoch 262/4000: 100%|██████████| 10/10 [00:00<00:00, 15.65it/s]
+Epoch 262/4000: 100%|██████████| 10/10 [00:01<00:00,  9.70it/s]
+epoch: 261, beta = 0.001681, Train MSE: 0.000824, Train CE:0.000051, Train KL:2.316512, Val MSE:0.000827, Val CE:0.000052, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 263/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 263/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
+Epoch 263/4000:  40%|████      | 4/10 [00:00<00:00,  7.13it/s]
+Epoch 263/4000:  70%|███████   | 7/10 [00:00<00:00, 11.76it/s]
+Epoch 263/4000: 100%|██████████| 10/10 [00:00<00:00, 15.28it/s]
+Epoch 263/4000: 100%|██████████| 10/10 [00:01<00:00,  9.54it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 264/4000:  40%|████      | 4/10 [00:00<00:00,  7.39it/s]
+Epoch 264/4000:  70%|███████   | 7/10 [00:00<00:00, 12.22it/s]
+Epoch 264/4000: 100%|██████████| 10/10 [00:00<00:00, 15.97it/s]
+Epoch 264/4000: 100%|██████████| 10/10 [00:00<00:00, 10.03it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 265/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 265/4000:  40%|████      | 4/10 [00:00<00:00,  7.09it/s]
+Epoch 265/4000:  70%|███████   | 7/10 [00:00<00:00, 11.84it/s]
+Epoch 265/4000: 100%|██████████| 10/10 [00:00<00:00, 15.63it/s]
+Epoch 265/4000: 100%|██████████| 10/10 [00:01<00:00,  9.77it/s]
+epoch: 264, beta = 0.001681, Train MSE: 0.000767, Train CE:0.000042, Train KL:2.379411, Val MSE:0.000752, Val CE:0.000042, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 266/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 266/4000:  10%|█         | 1/10 [00:00<00:04,  1.80it/s]
+Epoch 266/4000:  40%|████      | 4/10 [00:00<00:00,  7.21it/s]
+Epoch 266/4000:  70%|███████   | 7/10 [00:00<00:00, 12.16it/s]
+Epoch 266/4000: 100%|██████████| 10/10 [00:00<00:00, 15.80it/s]
+Epoch 266/4000: 100%|██████████| 10/10 [00:01<00:00,  9.38it/s]
+epoch: 265, beta = 0.001681, Train MSE: 0.000765, Train CE:0.000042, Train KL:2.373049, Val MSE:0.000795, Val CE:0.000043, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 267/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 267/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 267/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 267/4000:  70%|███████   | 7/10 [00:00<00:00, 11.60it/s]
+Epoch 267/4000: 100%|██████████| 10/10 [00:00<00:00, 15.22it/s]
+Epoch 267/4000: 100%|██████████| 10/10 [00:01<00:00,  9.45it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 268/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 268/4000:  70%|███████   | 7/10 [00:00<00:00, 12.28it/s]
+Epoch 268/4000: 100%|██████████| 10/10 [00:00<00:00, 16.04it/s]
+Epoch 268/4000: 100%|██████████| 10/10 [00:01<00:00,  9.80it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 269/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 269/4000:  40%|████      | 4/10 [00:00<00:00,  7.09it/s]
+Epoch 269/4000:  70%|███████   | 7/10 [00:00<00:00, 11.78it/s]
+Epoch 269/4000: 100%|██████████| 10/10 [00:00<00:00, 15.39it/s]
+Epoch 269/4000: 100%|██████████| 10/10 [00:01<00:00,  9.68it/s]
+epoch: 268, beta = 0.001681, Train MSE: 0.000819, Train CE:0.000043, Train KL:2.317440, Val MSE:0.000817, Val CE:0.000044, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 270/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 270/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 270/4000:  40%|████      | 4/10 [00:00<00:00,  6.70it/s]
+Epoch 270/4000:  70%|███████   | 7/10 [00:00<00:00, 11.31it/s]
+Epoch 270/4000: 100%|██████████| 10/10 [00:00<00:00, 14.79it/s]
+Epoch 270/4000: 100%|██████████| 10/10 [00:01<00:00,  9.26it/s]
+epoch: 269, beta = 0.001681, Train MSE: 0.000799, Train CE:0.000044, Train KL:2.319218, Val MSE:0.000798, Val CE:0.000045, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 271/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 271/4000:  10%|█         | 1/10 [00:00<00:05,  1.54it/s]
+Epoch 271/4000:  40%|████      | 4/10 [00:00<00:00,  6.38it/s]
+Epoch 271/4000:  70%|███████   | 7/10 [00:00<00:00, 10.98it/s]
+Epoch 271/4000: 100%|██████████| 10/10 [00:00<00:00, 14.82it/s]
+Epoch 271/4000: 100%|██████████| 10/10 [00:01<00:00,  8.96it/s]
+epoch: 270, beta = 0.001681, Train MSE: 0.000798, Train CE:0.000052, Train KL:2.327267, Val MSE:0.000840, Val CE:0.000042, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 272/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 272/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 272/4000:  40%|████      | 4/10 [00:00<00:00,  7.42it/s]
+Epoch 272/4000:  70%|███████   | 7/10 [00:00<00:00, 12.35it/s]
+Epoch 272/4000: 100%|██████████| 10/10 [00:00<00:00, 16.07it/s]
+Epoch 272/4000: 100%|██████████| 10/10 [00:00<00:00, 10.04it/s]
+epoch: 271, beta = 0.001681, Train MSE: 0.000790, Train CE:0.000042, Train KL:2.338233, Val MSE:0.000809, Val CE:0.000042, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 273/4000:  70%|███████   | 7/10 [00:00<00:00, 11.85it/s]
+Epoch 273/4000: 100%|██████████| 10/10 [00:00<00:00, 15.59it/s]
+Epoch 273/4000: 100%|██████████| 10/10 [00:01<00:00,  9.80it/s]
+epoch: 272, beta = 0.001681, Train MSE: 0.000797, Train CE:0.000043, Train KL:2.321905, Val MSE:0.000801, Val CE:0.000042, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 274/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 274/4000:  40%|████      | 4/10 [00:00<00:00,  7.00it/s]
+Epoch 274/4000:  70%|███████   | 7/10 [00:00<00:00, 11.80it/s]
+Epoch 274/4000: 100%|██████████| 10/10 [00:00<00:00, 15.13it/s]
+Epoch 274/4000: 100%|██████████| 10/10 [00:01<00:00,  9.48it/s]
+epoch: 273, beta = 0.001681, Train MSE: 0.000799, Train CE:0.000043, Train KL:2.311561, Val MSE:0.000795, Val CE:0.000043, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 275/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
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+Epoch 275/4000:  80%|████████  | 8/10 [00:00<00:00, 13.04it/s]
+Epoch 275/4000: 100%|██████████| 10/10 [00:01<00:00,  9.58it/s]
+epoch: 274, beta = 0.001176, Train MSE: 0.000792, Train CE:0.000043, Train KL:2.311066, Val MSE:0.000794, Val CE:0.000045, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 276/4000:  10%|█         | 1/10 [00:00<00:04,  1.80it/s]
+Epoch 276/4000:  40%|████      | 4/10 [00:00<00:00,  6.92it/s]
+Epoch 276/4000:  70%|███████   | 7/10 [00:00<00:00, 11.70it/s]
+Epoch 276/4000: 100%|██████████| 10/10 [00:00<00:00, 15.48it/s]
+Epoch 276/4000: 100%|██████████| 10/10 [00:01<00:00,  9.57it/s]
+Learning rate updated: 0.0007737809374999998
+epoch: 275, beta = 0.001176, Train MSE: 0.000768, Train CE:0.000043, Train KL:2.317920, Val MSE:0.000740, Val CE:0.000043, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 277/4000:  10%|█         | 1/10 [00:00<00:04,  1.87it/s]
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+Epoch 277/4000:  80%|████████  | 8/10 [00:00<00:00, 13.83it/s]
+Epoch 277/4000: 100%|██████████| 10/10 [00:00<00:00, 10.16it/s]
+epoch: 276, beta = 0.001176, Train MSE: 0.000713, Train CE:0.000047, Train KL:2.347719, Val MSE:0.000687, Val CE:0.000042, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 278/4000:  80%|████████  | 8/10 [00:00<00:00, 13.30it/s]
+Epoch 278/4000: 100%|██████████| 10/10 [00:00<00:00, 10.02it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 279/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 279/4000:  10%|█         | 1/10 [00:00<00:04,  1.89it/s]
+Epoch 279/4000:  40%|████      | 4/10 [00:00<00:00,  7.37it/s]
+Epoch 279/4000:  70%|███████   | 7/10 [00:00<00:00, 12.27it/s]
+Epoch 279/4000: 100%|██████████| 10/10 [00:00<00:00, 15.93it/s]
+Epoch 279/4000: 100%|██████████| 10/10 [00:01<00:00,  9.96it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 280/4000:  80%|████████  | 8/10 [00:00<00:00, 12.89it/s]
+Epoch 280/4000: 100%|██████████| 10/10 [00:01<00:00,  9.52it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 281/4000: 100%|██████████| 10/10 [00:00<00:00, 16.25it/s]
+Epoch 281/4000: 100%|██████████| 10/10 [00:00<00:00, 10.04it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 282/4000:  40%|████      | 4/10 [00:00<00:00,  7.01it/s]
+Epoch 282/4000:  70%|███████   | 7/10 [00:00<00:00, 11.65it/s]
+Epoch 282/4000: 100%|██████████| 10/10 [00:00<00:00, 14.96it/s]
+Epoch 282/4000: 100%|██████████| 10/10 [00:01<00:00,  9.30it/s]
+epoch: 281, beta = 0.001176, Train MSE: 0.000624, Train CE:0.000041, Train KL:2.400686, Val MSE:0.000632, Val CE:0.000041, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 283/4000:  10%|█         | 1/10 [00:00<00:05,  1.77it/s]
+Epoch 283/4000:  40%|████      | 4/10 [00:00<00:00,  7.13it/s]
+Epoch 283/4000:  80%|████████  | 8/10 [00:00<00:00, 13.36it/s]
+Epoch 283/4000: 100%|██████████| 10/10 [00:01<00:00,  9.86it/s]
+epoch: 282, beta = 0.001176, Train MSE: 0.000618, Train CE:0.000041, Train KL:2.403365, Val MSE:0.000625, Val CE:0.000041, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 284/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 284/4000:  40%|████      | 4/10 [00:00<00:00,  6.96it/s]
+Epoch 284/4000:  70%|███████   | 7/10 [00:00<00:00, 11.76it/s]
+Epoch 284/4000: 100%|██████████| 10/10 [00:00<00:00, 15.35it/s]
+Epoch 284/4000: 100%|██████████| 10/10 [00:01<00:00,  9.66it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 287/4000:  10%|█         | 1/10 [00:00<00:04,  1.87it/s]
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+Epoch 287/4000:  70%|███████   | 7/10 [00:00<00:00, 12.01it/s]
+Epoch 287/4000: 100%|██████████| 10/10 [00:00<00:00, 15.84it/s]
+Epoch 287/4000: 100%|██████████| 10/10 [00:01<00:00,  9.78it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 288/4000:  40%|████      | 4/10 [00:00<00:00,  6.59it/s]
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+Epoch 288/4000: 100%|██████████| 10/10 [00:00<00:00, 14.11it/s]
+Epoch 288/4000: 100%|██████████| 10/10 [00:01<00:00,  8.92it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 291/4000:  30%|███       | 3/10 [00:00<00:01,  5.55it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 296/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 296/4000:  70%|███████   | 7/10 [00:00<00:00, 11.61it/s]
+Epoch 296/4000: 100%|██████████| 10/10 [00:00<00:00, 15.67it/s]
+Epoch 296/4000: 100%|██████████| 10/10 [00:01<00:00,  9.54it/s]
+epoch: 295, beta = 0.001176, Train MSE: 0.000587, Train CE:0.000038, Train KL:2.393556, Val MSE:0.000594, Val CE:0.000038, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 297/4000:  40%|████      | 4/10 [00:00<00:00,  7.38it/s]
+Epoch 297/4000:  70%|███████   | 7/10 [00:00<00:00, 12.18it/s]
+Epoch 297/4000: 100%|██████████| 10/10 [00:00<00:00, 15.93it/s]
+Epoch 297/4000: 100%|██████████| 10/10 [00:01<00:00,  9.96it/s]
+epoch: 296, beta = 0.001176, Train MSE: 0.000579, Train CE:0.000077, Train KL:2.408659, Val MSE:0.000556, Val CE:0.000035, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 298/4000:  40%|████      | 4/10 [00:00<00:00,  6.85it/s]
+Epoch 298/4000:  80%|████████  | 8/10 [00:00<00:00, 13.01it/s]
+Epoch 298/4000: 100%|██████████| 10/10 [00:01<00:00,  9.64it/s]
+epoch: 297, beta = 0.001176, Train MSE: 0.000554, Train CE:0.000034, Train KL:2.441980, Val MSE:0.000570, Val CE:0.000034, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 299/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
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+Epoch 299/4000:  80%|████████  | 8/10 [00:00<00:00, 13.04it/s]
+Epoch 299/4000: 100%|██████████| 10/10 [00:01<00:00,  9.72it/s]
+epoch: 298, beta = 0.001176, Train MSE: 0.000562, Train CE:0.000034, Train KL:2.429691, Val MSE:0.000584, Val CE:0.000035, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 300/4000:  10%|█         | 1/10 [00:00<00:05,  1.61it/s]
+Epoch 300/4000:  30%|███       | 3/10 [00:00<00:01,  5.01it/s]
+Epoch 300/4000:  60%|██████    | 6/10 [00:00<00:00,  9.64it/s]
+Epoch 300/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.93it/s]
+Epoch 300/4000: 100%|██████████| 10/10 [00:01<00:00,  8.94it/s]
+epoch: 299, beta = 0.001176, Train MSE: 0.000578, Train CE:0.000035, Train KL:2.406280, Val MSE:0.000632, Val CE:0.000034, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 303/4000: 100%|██████████| 10/10 [00:00<00:00, 15.93it/s]
+Epoch 303/4000: 100%|██████████| 10/10 [00:00<00:00, 10.02it/s]
+epoch: 302, beta = 0.001176, Train MSE: 0.000572, Train CE:0.000035, Train KL:2.394200, Val MSE:0.000579, Val CE:0.000036, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 304/4000: 100%|██████████| 10/10 [00:01<00:00,  9.78it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 305/4000:  70%|███████   | 7/10 [00:00<00:00, 12.06it/s]
+Epoch 305/4000: 100%|██████████| 10/10 [00:00<00:00, 15.99it/s]
+Epoch 305/4000: 100%|██████████| 10/10 [00:01<00:00,  9.96it/s]
+epoch: 304, beta = 0.001176, Train MSE: 0.000566, Train CE:0.000039, Train KL:2.393976, Val MSE:0.000562, Val CE:0.000036, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 306/4000:  70%|███████   | 7/10 [00:00<00:00, 11.98it/s]
+Epoch 306/4000: 100%|██████████| 10/10 [00:00<00:00, 15.65it/s]
+Epoch 306/4000: 100%|██████████| 10/10 [00:01<00:00,  9.81it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 307/4000: 100%|██████████| 10/10 [00:00<00:00, 10.13it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 308/4000:  40%|████      | 4/10 [00:00<00:00,  7.99it/s]
+Epoch 308/4000:  70%|███████   | 7/10 [00:00<00:00, 12.97it/s]
+Epoch 308/4000: 100%|██████████| 10/10 [00:00<00:00, 16.21it/s]
+Epoch 308/4000: 100%|██████████| 10/10 [00:00<00:00, 10.47it/s]
+epoch: 307, beta = 0.000824, Train MSE: 0.000572, Train CE:0.000035, Train KL:2.387260, Val MSE:0.000584, Val CE:0.000035, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 309/4000: 100%|██████████| 10/10 [00:00<00:00, 10.16it/s]
+Learning rate updated: 0.0007350918906249997
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 310/4000:  70%|███████   | 7/10 [00:00<00:00, 12.29it/s]
+Epoch 310/4000: 100%|██████████| 10/10 [00:00<00:00, 16.17it/s]
+Epoch 310/4000: 100%|██████████| 10/10 [00:00<00:00, 10.03it/s]
+epoch: 309, beta = 0.000824, Train MSE: 0.000525, Train CE:0.000034, Train KL:2.424374, Val MSE:0.000524, Val CE:0.000034, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 311/4000:  70%|███████   | 7/10 [00:00<00:00, 11.76it/s]
+Epoch 311/4000: 100%|██████████| 10/10 [00:00<00:00, 15.43it/s]
+Epoch 311/4000: 100%|██████████| 10/10 [00:01<00:00,  9.41it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 312/4000:  80%|████████  | 8/10 [00:00<00:00, 13.87it/s]
+Epoch 312/4000: 100%|██████████| 10/10 [00:00<00:00, 10.33it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 313/4000: 100%|██████████| 10/10 [00:00<00:00, 16.71it/s]
+Epoch 313/4000: 100%|██████████| 10/10 [00:00<00:00, 10.45it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 315/4000:  80%|████████  | 8/10 [00:00<00:00, 12.96it/s]
+Epoch 315/4000: 100%|██████████| 10/10 [00:01<00:00,  9.63it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 316/4000:  80%|████████  | 8/10 [00:00<00:00, 13.37it/s]
+Epoch 316/4000: 100%|██████████| 10/10 [00:01<00:00,  9.99it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 317/4000: 100%|██████████| 10/10 [00:00<00:00, 16.60it/s]
+Epoch 317/4000: 100%|██████████| 10/10 [00:00<00:00, 10.41it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 320/4000: 100%|██████████| 10/10 [00:00<00:00, 15.99it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
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+Epoch 324/4000:  40%|████      | 4/10 [00:00<00:00,  7.67it/s]
+Epoch 324/4000:  80%|████████  | 8/10 [00:00<00:00, 14.15it/s]
+Epoch 324/4000: 100%|██████████| 10/10 [00:00<00:00, 10.51it/s]
+epoch: 323, beta = 0.000824, Train MSE: 0.000436, Train CE:0.000029, Train KL:2.496719, Val MSE:0.000441, Val CE:0.000029, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 325/4000:  10%|█         | 1/10 [00:00<00:04,  2.04it/s]
+Epoch 325/4000:  40%|████      | 4/10 [00:00<00:00,  7.77it/s]
+Epoch 325/4000:  70%|███████   | 7/10 [00:00<00:00, 12.65it/s]
+Epoch 325/4000: 100%|██████████| 10/10 [00:00<00:00, 16.51it/s]
+Epoch 325/4000: 100%|██████████| 10/10 [00:00<00:00, 10.13it/s]
+epoch: 324, beta = 0.000824, Train MSE: 0.000440, Train CE:0.000029, Train KL:2.494767, Val MSE:0.000448, Val CE:0.000029, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 326/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 326/4000:  10%|█         | 1/10 [00:00<00:05,  1.62it/s]
+Epoch 326/4000:  40%|████      | 4/10 [00:00<00:00,  6.73it/s]
+Epoch 326/4000:  80%|████████  | 8/10 [00:00<00:00, 12.62it/s]
+Epoch 326/4000: 100%|██████████| 10/10 [00:01<00:00,  9.40it/s]
+epoch: 325, beta = 0.000576, Train MSE: 0.000438, Train CE:0.000029, Train KL:2.493476, Val MSE:0.000436, Val CE:0.000029, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 327/4000:  10%|█         | 1/10 [00:00<00:04,  1.99it/s]
+Epoch 327/4000:  40%|████      | 4/10 [00:00<00:00,  7.88it/s]
+Epoch 327/4000:  80%|████████  | 8/10 [00:00<00:00, 14.42it/s]
+Epoch 327/4000: 100%|██████████| 10/10 [00:00<00:00, 10.70it/s]
+Learning rate updated: 0.0006983372960937497
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 328/4000:  70%|███████   | 7/10 [00:00<00:00, 12.45it/s]
+Epoch 328/4000: 100%|██████████| 10/10 [00:00<00:00, 16.16it/s]
+Epoch 328/4000: 100%|██████████| 10/10 [00:00<00:00, 10.15it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 329/4000:  70%|███████   | 7/10 [00:00<00:00, 12.31it/s]
+Epoch 329/4000: 100%|██████████| 10/10 [00:00<00:00, 16.19it/s]
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+
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+Epoch 330/4000: 100%|██████████| 10/10 [00:01<00:00,  8.92it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 331/4000: 100%|██████████| 10/10 [00:00<00:00, 15.28it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 334/4000: 100%|██████████| 10/10 [00:00<00:00, 15.12it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
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+epoch: 402, beta = 0.000576, Train MSE: 0.000291, Train CE:0.000016, Train KL:2.605190, Val MSE:0.000293, Val CE:0.000016, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 404/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 404/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
+Epoch 404/4000:  40%|████      | 4/10 [00:00<00:00,  6.94it/s]
+Epoch 404/4000:  70%|███████   | 7/10 [00:00<00:00, 11.72it/s]
+Epoch 404/4000: 100%|██████████| 10/10 [00:00<00:00, 15.47it/s]
+Epoch 404/4000: 100%|██████████| 10/10 [00:01<00:00,  9.64it/s]
+epoch: 403, beta = 0.000576, Train MSE: 0.000290, Train CE:0.000016, Train KL:2.599176, Val MSE:0.000292, Val CE:0.000016, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 405/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 405/4000:  10%|█         | 1/10 [00:00<00:05,  1.77it/s]
+Epoch 405/4000:  30%|███       | 3/10 [00:00<00:01,  5.42it/s]
+Epoch 405/4000:  60%|██████    | 6/10 [00:00<00:00, 10.24it/s]
+Epoch 405/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.71it/s]
+Epoch 405/4000: 100%|██████████| 10/10 [00:01<00:00,  8.70it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 406/4000: 100%|██████████| 10/10 [00:00<00:00, 15.36it/s]
+Epoch 406/4000: 100%|██████████| 10/10 [00:01<00:00,  9.66it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 407/4000:  30%|███       | 3/10 [00:00<00:01,  5.65it/s]
+Epoch 407/4000:  60%|██████    | 6/10 [00:00<00:00, 10.68it/s]
+Epoch 407/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.89it/s]
+Epoch 407/4000: 100%|██████████| 10/10 [00:01<00:00,  9.44it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 408/4000:  40%|████      | 4/10 [00:00<00:00,  6.81it/s]
+Epoch 408/4000:  70%|███████   | 7/10 [00:00<00:00, 11.28it/s]
+Epoch 408/4000: 100%|██████████| 10/10 [00:00<00:00, 14.59it/s]
+Epoch 408/4000: 100%|██████████| 10/10 [00:01<00:00,  9.49it/s]
+epoch: 407, beta = 0.000404, Train MSE: 0.000284, Train CE:0.000016, Train KL:2.583570, Val MSE:0.000286, Val CE:0.000016, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 409/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.93it/s]
+Epoch 409/4000: 100%|██████████| 10/10 [00:00<00:00, 10.14it/s]
+Learning rate updated: 0.0006634204312890621
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 412/4000: 100%|██████████| 10/10 [00:00<00:00, 14.45it/s]
+Epoch 412/4000: 100%|██████████| 10/10 [00:01<00:00,  9.34it/s]
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+Epoch 415/4000: 100%|██████████| 10/10 [00:00<00:00, 15.99it/s]
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+Epoch 416/4000: 100%|██████████| 10/10 [00:00<00:00, 15.90it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 418/4000: 100%|██████████| 10/10 [00:00<00:00, 16.93it/s]
+Epoch 418/4000: 100%|██████████| 10/10 [00:00<00:00, 10.80it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 419/4000: 100%|██████████| 10/10 [00:01<00:00, 13.16it/s]
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+epoch: 418, beta = 0.000404, Train MSE: 0.000226, Train CE:0.000016, Train KL:2.668884, Val MSE:0.000227, Val CE:0.000016, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 420/4000:  70%|███████   | 7/10 [00:00<00:00, 11.94it/s]
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+Epoch 420/4000: 100%|██████████| 10/10 [00:01<00:00,  9.74it/s]
+Learning rate updated: 0.000630249409724609
+epoch: 419, beta = 0.000404, Train MSE: 0.000225, Train CE:0.000016, Train KL:2.669239, Val MSE:0.000226, Val CE:0.000016, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 426/4000: 100%|██████████| 10/10 [00:00<00:00, 11.07it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 427/4000: 100%|██████████| 10/10 [00:00<00:00, 16.02it/s]
+Epoch 427/4000: 100%|██████████| 10/10 [00:00<00:00, 10.04it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+
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+Epoch 430/4000:  70%|███████   | 7/10 [00:00<00:00, 12.34it/s]
+Epoch 430/4000: 100%|██████████| 10/10 [00:00<00:00, 15.36it/s]
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+epoch: 429, beta = 0.000404, Train MSE: 0.000214, Train CE:0.000015, Train KL:2.674895, Val MSE:0.000214, Val CE:0.000016, Train ACC:1.000000, Val ACC:1.000000
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+Learning rate updated: 0.0005987369392383785
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+
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+Epoch 508/4000:  70%|███████   | 7/10 [00:00<00:00, 10.84it/s]
+Epoch 508/4000: 100%|██████████| 10/10 [00:00<00:00, 13.66it/s]
+Epoch 508/4000: 100%|██████████| 10/10 [00:01<00:00,  8.93it/s]
+epoch: 507, beta = 0.000404, Train MSE: 0.000193, Train CE:0.000011, Train KL:2.633564, Val MSE:0.000199, Val CE:0.000011, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 509/4000:  30%|███       | 3/10 [00:00<00:01,  5.30it/s]
+Epoch 509/4000:  60%|██████    | 6/10 [00:00<00:00,  9.77it/s]
+Epoch 509/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.25it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 510/4000: 100%|██████████| 10/10 [00:00<00:00, 15.22it/s]
+Epoch 510/4000: 100%|██████████| 10/10 [00:01<00:00,  9.52it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 511/4000:  60%|██████    | 6/10 [00:00<00:00,  9.77it/s]
+Epoch 511/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.03it/s]
+Epoch 511/4000: 100%|██████████| 10/10 [00:01<00:00,  9.27it/s]
+epoch: 510, beta = 0.000404, Train MSE: 0.000192, Train CE:0.000011, Train KL:2.608481, Val MSE:0.000204, Val CE:0.000011, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 512/4000: 100%|██████████| 10/10 [00:00<00:00, 14.66it/s]
+Epoch 512/4000: 100%|██████████| 10/10 [00:01<00:00,  8.84it/s]
+epoch: 511, beta = 0.000404, Train MSE: 0.000194, Train CE:0.000011, Train KL:2.607525, Val MSE:0.000186, Val CE:0.000011, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 513/4000:  70%|███████   | 7/10 [00:00<00:00, 11.61it/s]
+Epoch 513/4000: 100%|██████████| 10/10 [00:00<00:00, 14.54it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 515/4000:  70%|███████   | 7/10 [00:00<00:00,  9.91it/s]
+Epoch 515/4000: 100%|██████████| 10/10 [00:01<00:00, 13.30it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 516/4000:  30%|███       | 3/10 [00:00<00:01,  5.46it/s]
+Epoch 516/4000:  60%|██████    | 6/10 [00:00<00:00, 10.01it/s]
+Epoch 516/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.52it/s]
+Epoch 516/4000: 100%|██████████| 10/10 [00:01<00:00,  8.92it/s]
+epoch: 515, beta = 0.000282, Train MSE: 0.000183, Train CE:0.000011, Train KL:2.601100, Val MSE:0.000186, Val CE:0.000011, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 517/4000:  90%|█████████ | 9/10 [00:00<00:00, 12.59it/s]
+Epoch 517/4000: 100%|██████████| 10/10 [00:01<00:00,  8.82it/s]
+Learning rate updated: 0.0005688000922764595
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 518/4000: 100%|██████████| 10/10 [00:01<00:00, 14.15it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 519/4000: 100%|██████████| 10/10 [00:00<00:00, 15.47it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 522/4000: 100%|██████████| 10/10 [00:00<00:00, 14.80it/s]
+Epoch 522/4000: 100%|██████████| 10/10 [00:01<00:00,  9.32it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 523/4000: 100%|██████████| 10/10 [00:00<00:00, 16.04it/s]
+Epoch 523/4000: 100%|██████████| 10/10 [00:00<00:00, 10.23it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 524/4000: 100%|██████████| 10/10 [00:00<00:00, 14.79it/s]
+Epoch 524/4000: 100%|██████████| 10/10 [00:01<00:00,  9.41it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 531/4000: 100%|██████████| 10/10 [00:00<00:00, 10.59it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 560/4000:  70%|███████   | 7/10 [00:00<00:00, 11.35it/s]
+Epoch 560/4000: 100%|██████████| 10/10 [00:00<00:00, 14.34it/s]
+Epoch 560/4000: 100%|██████████| 10/10 [00:01<00:00,  9.15it/s]
+epoch: 559, beta = 0.000282, Train MSE: 0.000141, Train CE:0.000012, Train KL:2.767079, Val MSE:0.000133, Val CE:0.000011, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 561/4000:  40%|████      | 4/10 [00:00<00:01,  5.98it/s]
+Epoch 561/4000:  70%|███████   | 7/10 [00:00<00:00, 10.16it/s]
+Epoch 561/4000: 100%|██████████| 10/10 [00:01<00:00, 13.39it/s]
+Epoch 561/4000: 100%|██████████| 10/10 [00:01<00:00,  8.41it/s]
+epoch: 560, beta = 0.000282, Train MSE: 0.000133, Train CE:0.000012, Train KL:2.751797, Val MSE:0.000129, Val CE:0.000011, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 562/4000:  40%|████      | 4/10 [00:00<00:00,  7.90it/s]
+Epoch 562/4000:  70%|███████   | 7/10 [00:00<00:00, 12.42it/s]
+Epoch 562/4000: 100%|██████████| 10/10 [00:00<00:00, 15.95it/s]
+Epoch 562/4000: 100%|██████████| 10/10 [00:01<00:00,  9.93it/s]
+epoch: 561, beta = 0.000282, Train MSE: 0.000132, Train CE:0.000011, Train KL:2.731330, Val MSE:0.000135, Val CE:0.000011, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 563/4000:  30%|███       | 3/10 [00:00<00:01,  5.29it/s]
+Epoch 563/4000:  60%|██████    | 6/10 [00:00<00:00,  9.87it/s]
+Epoch 563/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.58it/s]
+Epoch 563/4000: 100%|██████████| 10/10 [00:01<00:00,  8.84it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 564/4000:  40%|████      | 4/10 [00:00<00:00,  7.50it/s]
+Epoch 564/4000:  70%|███████   | 7/10 [00:00<00:00, 12.19it/s]
+Epoch 564/4000: 100%|██████████| 10/10 [00:00<00:00, 15.77it/s]
+Epoch 564/4000: 100%|██████████| 10/10 [00:00<00:00, 10.05it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 565/4000: 100%|██████████| 10/10 [00:00<00:00, 14.64it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 567/4000:  40%|████      | 4/10 [00:00<00:00,  7.90it/s]
+Epoch 567/4000:  70%|███████   | 7/10 [00:00<00:00, 12.64it/s]
+Epoch 567/4000: 100%|██████████| 10/10 [00:00<00:00, 16.17it/s]
+Epoch 567/4000: 100%|██████████| 10/10 [00:00<00:00, 10.45it/s]
+epoch: 566, beta = 0.000198, Train MSE: 0.000134, Train CE:0.000011, Train KL:2.678364, Val MSE:0.000134, Val CE:0.000010, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 568/4000: 100%|██████████| 10/10 [00:00<00:00, 16.50it/s]
+Epoch 568/4000: 100%|██████████| 10/10 [00:00<00:00, 10.39it/s]
+Learning rate updated: 0.0005403600876626365
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 569/4000: 100%|██████████| 10/10 [00:00<00:00, 15.67it/s]
+Epoch 569/4000: 100%|██████████| 10/10 [00:00<00:00, 10.00it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+
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+
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 574/4000: 100%|██████████| 10/10 [00:00<00:00, 16.08it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 575/4000: 100%|██████████| 10/10 [00:00<00:00, 16.07it/s]
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+
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+epoch: 1173, beta = 0.000033, Train MSE: 0.000021, Train CE:0.000001, Train KL:2.964451, Val MSE:0.000020, Val CE:0.000001, Train ACC:1.000000, Val ACC:1.000000
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+Learning rate updated: 0.0003773536025353072
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+epoch: 1199, beta = 0.000033, Train MSE: 0.000019, Train CE:0.000001, Train KL:3.046388, Val MSE:0.000026, Val CE:0.000001, Train ACC:1.000000, Val ACC:1.000000
+
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1303/4000:  70%|███████   | 7/10 [00:00<00:00, 10.51it/s]
+Epoch 1303/4000: 100%|██████████| 10/10 [00:00<00:00, 14.01it/s]
+Epoch 1303/4000: 100%|██████████| 10/10 [00:01<00:00,  8.78it/s]
+epoch: 1302, beta = 0.000033, Train MSE: 0.000014, Train CE:0.000000, Train KL:3.116140, Val MSE:0.000013, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1304/4000:  30%|███       | 3/10 [00:00<00:01,  5.38it/s]
+Epoch 1304/4000:  60%|██████    | 6/10 [00:00<00:00,  9.99it/s]
+Epoch 1304/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.57it/s]
+Epoch 1304/4000: 100%|██████████| 10/10 [00:01<00:00,  8.98it/s]
+epoch: 1303, beta = 0.000033, Train MSE: 0.000014, Train CE:0.000000, Train KL:3.102209, Val MSE:0.000013, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1305/4000:  40%|████      | 4/10 [00:00<00:00,  6.70it/s]
+Epoch 1305/4000:  70%|███████   | 7/10 [00:00<00:00, 10.97it/s]
+Epoch 1305/4000: 100%|██████████| 10/10 [00:00<00:00, 14.55it/s]
+Epoch 1305/4000: 100%|██████████| 10/10 [00:01<00:00,  9.05it/s]
+epoch: 1304, beta = 0.000033, Train MSE: 0.000014, Train CE:0.000000, Train KL:3.094600, Val MSE:0.000014, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 1306/4000:  40%|████      | 4/10 [00:00<00:00,  7.81it/s]
+Epoch 1306/4000:  70%|███████   | 7/10 [00:00<00:00, 12.66it/s]
+Epoch 1306/4000: 100%|██████████| 10/10 [00:00<00:00, 16.13it/s]
+Epoch 1306/4000: 100%|██████████| 10/10 [00:00<00:00, 10.16it/s]
+epoch: 1305, beta = 0.000033, Train MSE: 0.000013, Train CE:0.000000, Train KL:3.089041, Val MSE:0.000013, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1307/4000:  40%|████      | 4/10 [00:00<00:00,  7.13it/s]
+Epoch 1307/4000:  70%|███████   | 7/10 [00:00<00:00, 11.94it/s]
+Epoch 1307/4000: 100%|██████████| 10/10 [00:00<00:00, 16.03it/s]
+Epoch 1307/4000: 100%|██████████| 10/10 [00:01<00:00,  9.73it/s]
+epoch: 1306, beta = 0.000033, Train MSE: 0.000013, Train CE:0.000000, Train KL:3.080429, Val MSE:0.000014, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1308/4000:  40%|████      | 4/10 [00:00<00:00,  6.82it/s]
+Epoch 1308/4000:  70%|███████   | 7/10 [00:00<00:00, 11.16it/s]
+Epoch 1308/4000: 100%|██████████| 10/10 [00:00<00:00, 14.43it/s]
+Epoch 1308/4000: 100%|██████████| 10/10 [00:01<00:00,  9.08it/s]
+epoch: 1307, beta = 0.000023, Train MSE: 0.000013, Train CE:0.000000, Train KL:3.074319, Val MSE:0.000013, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1309/4000:  40%|████      | 4/10 [00:00<00:00,  6.82it/s]
+Epoch 1309/4000:  70%|███████   | 7/10 [00:00<00:00, 11.53it/s]
+Epoch 1309/4000: 100%|██████████| 10/10 [00:00<00:00, 15.24it/s]
+Epoch 1309/4000: 100%|██████████| 10/10 [00:01<00:00,  9.34it/s]
+Learning rate updated: 0.0003584859224085418
+epoch: 1308, beta = 0.000023, Train MSE: 0.000013, Train CE:0.000000, Train KL:3.085778, Val MSE:0.000012, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+epoch: 1309, beta = 0.000023, Train MSE: 0.000011, Train CE:0.000000, Train KL:3.129298, Val MSE:0.000011, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1311/4000: 100%|██████████| 10/10 [00:00<00:00, 15.28it/s]
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+epoch: 1310, beta = 0.000023, Train MSE: 0.000011, Train CE:0.000000, Train KL:3.153288, Val MSE:0.000011, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 1312/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.09it/s]
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+Epoch 1316/4000: 100%|██████████| 10/10 [00:00<00:00, 14.93it/s]
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+epoch: 1317, beta = 0.000023, Train MSE: 0.000011, Train CE:0.000000, Train KL:3.149800, Val MSE:0.000010, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1319/4000:  70%|███████   | 7/10 [00:00<00:00, 11.55it/s]
+Epoch 1319/4000: 100%|██████████| 10/10 [00:00<00:00, 15.05it/s]
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+epoch: 1318, beta = 0.000023, Train MSE: 0.000011, Train CE:0.000000, Train KL:3.148649, Val MSE:0.000011, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1320/4000: 100%|██████████| 10/10 [00:01<00:00,  8.77it/s]
+Learning rate updated: 0.0003405616262881147
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1329/4000:  70%|███████   | 7/10 [00:00<00:00, 10.48it/s]
+Epoch 1329/4000: 100%|██████████| 10/10 [00:01<00:00, 13.95it/s]
+Epoch 1329/4000: 100%|██████████| 10/10 [00:01<00:00,  8.67it/s]
+epoch: 1328, beta = 0.000023, Train MSE: 0.000010, Train CE:0.000000, Train KL:3.139262, Val MSE:0.000010, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 1330/4000:  70%|███████   | 7/10 [00:00<00:00, 11.20it/s]
+Epoch 1330/4000: 100%|██████████| 10/10 [00:00<00:00, 15.06it/s]
+Epoch 1330/4000: 100%|██████████| 10/10 [00:01<00:00,  9.30it/s]
+epoch: 1329, beta = 0.000023, Train MSE: 0.000010, Train CE:0.000000, Train KL:3.141370, Val MSE:0.000010, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 1331/4000:  70%|███████   | 7/10 [00:00<00:00, 10.63it/s]
+Epoch 1331/4000: 100%|██████████| 10/10 [00:01<00:00, 13.87it/s]
+Epoch 1331/4000: 100%|██████████| 10/10 [00:01<00:00,  8.78it/s]
+Learning rate updated: 0.00032353354497370894
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+Epoch 1332/4000:  70%|███████   | 7/10 [00:00<00:00, 11.24it/s]
+Epoch 1332/4000: 100%|██████████| 10/10 [00:00<00:00, 14.90it/s]
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+epoch: 1331, beta = 0.000023, Train MSE: 0.000010, Train CE:0.000000, Train KL:3.138409, Val MSE:0.000011, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 1333/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.11it/s]
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+Epoch 1337/4000: 100%|██████████| 10/10 [00:01<00:00, 14.46it/s]
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+Epoch 1338/4000:  90%|█████████ | 9/10 [00:00<00:00, 12.62it/s]
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+epoch: 1339, beta = 0.000023, Train MSE: 0.000010, Train CE:0.000000, Train KL:3.131488, Val MSE:0.000010, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+epoch: 1340, beta = 0.000023, Train MSE: 0.000010, Train CE:0.000000, Train KL:3.130038, Val MSE:0.000011, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 1342/4000: 100%|██████████| 10/10 [00:00<00:00, 15.22it/s]
+Epoch 1342/4000: 100%|██████████| 10/10 [00:01<00:00,  9.50it/s]
+Learning rate updated: 0.00030735686772502346
+epoch: 1341, beta = 0.000023, Train MSE: 0.000010, Train CE:0.000000, Train KL:3.130266, Val MSE:0.000010, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+epoch: 1342, beta = 0.000023, Train MSE: 0.000010, Train CE:0.000000, Train KL:3.129909, Val MSE:0.000010, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+epoch: 1343, beta = 0.000023, Train MSE: 0.000010, Train CE:0.000000, Train KL:3.128930, Val MSE:0.000010, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 1352/4000: 100%|██████████| 10/10 [00:00<00:00, 16.35it/s]
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+Learning rate updated: 0.00029198902433877225
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+Learning rate updated: 0.0002503440897424548
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+epoch: 1404, beta = 0.000023, Train MSE: 0.000011, Train CE:0.000000, Train KL:3.103340, Val MSE:0.000010, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 1406/4000: 100%|██████████| 10/10 [00:00<00:00, 14.83it/s]
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+epoch: 1405, beta = 0.000016, Train MSE: 0.000013, Train CE:0.000000, Train KL:3.102034, Val MSE:0.000017, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 1407/4000: 100%|██████████| 10/10 [00:01<00:00,  9.08it/s]
+Learning rate updated: 0.00023782688525533205
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+epoch: 1610, beta = 0.000008, Train MSE: 0.000006, Train CE:0.000000, Train KL:3.426287, Val MSE:0.000007, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
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+Epoch 1612/4000: 100%|██████████| 10/10 [00:00<00:00, 14.07it/s]
+Epoch 1612/4000: 100%|██████████| 10/10 [00:01<00:00,  9.05it/s]
+Learning rate updated: 0.00021463876394293716
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1613/4000: 100%|██████████| 10/10 [00:00<00:00, 15.11it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Learning rate updated: 0.00018402591023557573
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1893/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.38it/s]
+Epoch 1893/4000: 100%|██████████| 10/10 [00:01<00:00,  9.22it/s]
+epoch: 1892, beta = 0.000008, Train MSE: 0.000005, Train CE:0.000000, Train KL:3.377925, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1894/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.49it/s]
+Epoch 1894/4000: 100%|██████████| 10/10 [00:01<00:00,  8.78it/s]
+Learning rate updated: 0.00017482461472379692
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1895/4000:  40%|████      | 4/10 [00:00<00:00,  6.36it/s]
+Epoch 1895/4000:  70%|███████   | 7/10 [00:00<00:00, 10.75it/s]
+Epoch 1895/4000: 100%|██████████| 10/10 [00:00<00:00, 14.42it/s]
+Epoch 1895/4000: 100%|██████████| 10/10 [00:01<00:00,  8.85it/s]
+epoch: 1894, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.375422, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1896/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1896/4000:  10%|█         | 1/10 [00:00<00:06,  1.50it/s]
+Epoch 1896/4000:  30%|███       | 3/10 [00:00<00:01,  4.67it/s]
+Epoch 1896/4000:  50%|█████     | 5/10 [00:00<00:00,  7.68it/s]
+Epoch 1896/4000:  80%|████████  | 8/10 [00:01<00:00, 11.48it/s]
+Epoch 1896/4000: 100%|██████████| 10/10 [00:01<00:00,  8.04it/s]
+epoch: 1895, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.375335, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1897/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1897/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 1897/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 1897/4000:  70%|███████   | 7/10 [00:00<00:00, 11.03it/s]
+Epoch 1897/4000: 100%|██████████| 10/10 [00:00<00:00, 14.35it/s]
+Epoch 1897/4000: 100%|██████████| 10/10 [00:01<00:00,  9.11it/s]
+epoch: 1896, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.376281, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1898/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 1898/4000:  40%|████      | 4/10 [00:00<00:00,  7.10it/s]
+Epoch 1898/4000:  70%|███████   | 7/10 [00:00<00:00, 11.59it/s]
+Epoch 1898/4000: 100%|██████████| 10/10 [00:00<00:00, 15.18it/s]
+Epoch 1898/4000: 100%|██████████| 10/10 [00:01<00:00,  9.46it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1899/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 1899/4000:  40%|████      | 4/10 [00:00<00:00,  6.58it/s]
+Epoch 1899/4000:  70%|███████   | 7/10 [00:00<00:00, 10.87it/s]
+Epoch 1899/4000: 100%|██████████| 10/10 [00:00<00:00, 13.95it/s]
+Epoch 1899/4000: 100%|██████████| 10/10 [00:01<00:00,  8.72it/s]
+epoch: 1898, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.375388, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1900/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1900/4000:  10%|█         | 1/10 [00:00<00:05,  1.79it/s]
+Epoch 1900/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 1900/4000:  70%|███████   | 7/10 [00:00<00:00, 11.09it/s]
+Epoch 1900/4000: 100%|██████████| 10/10 [00:00<00:00, 14.93it/s]
+Epoch 1900/4000: 100%|██████████| 10/10 [00:01<00:00,  9.16it/s]
+epoch: 1899, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.372329, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1901/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1901/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
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+Epoch 1901/4000:  60%|██████    | 6/10 [00:00<00:00,  9.59it/s]
+Epoch 1901/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.29it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1902/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
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+Epoch 1902/4000: 100%|██████████| 10/10 [00:00<00:00, 14.81it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1903/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
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+Epoch 1903/4000:  70%|███████   | 7/10 [00:00<00:00, 11.56it/s]
+Epoch 1903/4000: 100%|██████████| 10/10 [00:00<00:00, 15.51it/s]
+Epoch 1903/4000: 100%|██████████| 10/10 [00:01<00:00,  9.27it/s]
+epoch: 1902, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.372345, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1904/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1904/4000:  10%|█         | 1/10 [00:00<00:05,  1.65it/s]
+Epoch 1904/4000:  40%|████      | 4/10 [00:00<00:00,  6.56it/s]
+Epoch 1904/4000:  70%|███████   | 7/10 [00:00<00:00, 11.00it/s]
+Epoch 1904/4000: 100%|██████████| 10/10 [00:00<00:00, 14.45it/s]
+Epoch 1904/4000: 100%|██████████| 10/10 [00:01<00:00,  8.86it/s]
+epoch: 1903, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.368109, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1905/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1905/4000:  40%|████      | 4/10 [00:00<00:00,  6.86it/s]
+Epoch 1905/4000:  70%|███████   | 7/10 [00:00<00:00, 11.59it/s]
+Epoch 1905/4000: 100%|██████████| 10/10 [00:00<00:00, 15.53it/s]
+Epoch 1905/4000: 100%|██████████| 10/10 [00:01<00:00,  9.47it/s]
+Learning rate updated: 0.00016608338398760707
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1906/4000: 100%|██████████| 10/10 [00:01<00:00, 13.94it/s]
+Epoch 1906/4000: 100%|██████████| 10/10 [00:01<00:00,  8.48it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1907/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
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+Epoch 1907/4000: 100%|██████████| 10/10 [00:00<00:00, 14.00it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1908/4000: 100%|██████████| 10/10 [00:00<00:00, 15.24it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1910/4000: 100%|██████████| 10/10 [00:00<00:00, 14.48it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1911/4000:  10%|█         | 1/10 [00:00<00:05,  1.62it/s]
+Epoch 1911/4000:  40%|████      | 4/10 [00:00<00:00,  6.50it/s]
+Epoch 1911/4000:  70%|███████   | 7/10 [00:00<00:00, 10.61it/s]
+Epoch 1911/4000: 100%|██████████| 10/10 [00:01<00:00, 13.69it/s]
+Epoch 1911/4000: 100%|██████████| 10/10 [00:01<00:00,  8.67it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1912/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 1912/4000:  30%|███       | 3/10 [00:00<00:01,  5.08it/s]
+Epoch 1912/4000:  50%|█████     | 5/10 [00:00<00:00,  8.05it/s]
+Epoch 1912/4000:  80%|████████  | 8/10 [00:00<00:00, 12.34it/s]
+Epoch 1912/4000: 100%|██████████| 10/10 [00:01<00:00,  8.08it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1913/4000: 100%|██████████| 10/10 [00:01<00:00,  9.08it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1914/4000: 100%|██████████| 10/10 [00:01<00:00, 13.39it/s]
+Epoch 1914/4000: 100%|██████████| 10/10 [00:01<00:00,  8.38it/s]
+epoch: 1913, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.367178, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1915/4000:  70%|███████   | 7/10 [00:00<00:00, 10.72it/s]
+Epoch 1915/4000: 100%|██████████| 10/10 [00:01<00:00, 13.54it/s]
+Epoch 1915/4000: 100%|██████████| 10/10 [00:01<00:00,  8.75it/s]
+epoch: 1914, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.366386, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1916/4000:  60%|██████    | 6/10 [00:00<00:00,  9.90it/s]
+Epoch 1916/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.93it/s]
+Epoch 1916/4000: 100%|██████████| 10/10 [00:01<00:00,  8.96it/s]
+Learning rate updated: 0.0001577792147882267
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1917/4000:  70%|███████   | 7/10 [00:00<00:00, 10.59it/s]
+Epoch 1917/4000: 100%|██████████| 10/10 [00:01<00:00, 13.68it/s]
+Epoch 1917/4000: 100%|██████████| 10/10 [00:01<00:00,  8.68it/s]
+epoch: 1916, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.368074, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1918/4000:  70%|███████   | 7/10 [00:00<00:00, 11.54it/s]
+Epoch 1918/4000: 100%|██████████| 10/10 [00:00<00:00, 14.88it/s]
+Epoch 1918/4000: 100%|██████████| 10/10 [00:01<00:00,  9.39it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1919/4000:  40%|████      | 4/10 [00:00<00:00,  6.72it/s]
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+Epoch 1919/4000: 100%|██████████| 10/10 [00:00<00:00, 14.84it/s]
+Epoch 1919/4000: 100%|██████████| 10/10 [00:01<00:00,  9.12it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1920/4000: 100%|██████████| 10/10 [00:00<00:00, 14.16it/s]
+Epoch 1920/4000: 100%|██████████| 10/10 [00:01<00:00,  9.03it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 1921/4000:  40%|████      | 4/10 [00:00<00:00,  6.66it/s]
+Epoch 1921/4000:  70%|███████   | 7/10 [00:00<00:00, 11.06it/s]
+Epoch 1921/4000: 100%|██████████| 10/10 [00:00<00:00, 14.64it/s]
+Epoch 1921/4000: 100%|██████████| 10/10 [00:01<00:00,  9.10it/s]
+epoch: 1920, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.363334, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1922/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1922/4000:  10%|█         | 1/10 [00:00<00:04,  1.93it/s]
+Epoch 1922/4000:  40%|████      | 4/10 [00:00<00:00,  7.53it/s]
+Epoch 1922/4000:  70%|███████   | 7/10 [00:00<00:00, 12.49it/s]
+Epoch 1922/4000: 100%|██████████| 10/10 [00:00<00:00, 16.42it/s]
+Epoch 1922/4000: 100%|██████████| 10/10 [00:00<00:00, 10.21it/s]
+epoch: 1921, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.362156, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1923/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1923/4000:  10%|█         | 1/10 [00:00<00:04,  1.93it/s]
+Epoch 1923/4000:  40%|████      | 4/10 [00:00<00:00,  7.25it/s]
+Epoch 1923/4000:  70%|███████   | 7/10 [00:00<00:00, 11.33it/s]
+Epoch 1923/4000: 100%|██████████| 10/10 [00:00<00:00, 14.59it/s]
+Epoch 1923/4000: 100%|██████████| 10/10 [00:01<00:00,  9.40it/s]
+epoch: 1922, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.366392, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1924/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1924/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 1924/4000:  40%|████      | 4/10 [00:00<00:00,  7.22it/s]
+Epoch 1924/4000:  70%|███████   | 7/10 [00:00<00:00, 12.16it/s]
+Epoch 1924/4000: 100%|██████████| 10/10 [00:00<00:00, 15.42it/s]
+Epoch 1924/4000: 100%|██████████| 10/10 [00:01<00:00,  9.38it/s]
+epoch: 1923, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.365365, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1925/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1925/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 1925/4000:  40%|████      | 4/10 [00:00<00:00,  6.56it/s]
+Epoch 1925/4000:  60%|██████    | 6/10 [00:00<00:00,  9.27it/s]
+Epoch 1925/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.01it/s]
+Epoch 1925/4000: 100%|██████████| 10/10 [00:01<00:00,  8.54it/s]
+epoch: 1924, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.360733, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1926/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1926/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 1926/4000:  40%|████      | 4/10 [00:00<00:00,  6.72it/s]
+Epoch 1926/4000:  70%|███████   | 7/10 [00:00<00:00, 10.96it/s]
+Epoch 1926/4000: 100%|██████████| 10/10 [00:00<00:00, 14.09it/s]
+Epoch 1926/4000: 100%|██████████| 10/10 [00:01<00:00,  8.99it/s]
+epoch: 1925, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.360427, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1927/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1927/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 1927/4000:  40%|████      | 4/10 [00:00<00:00,  6.65it/s]
+Epoch 1927/4000:  70%|███████   | 7/10 [00:00<00:00, 11.02it/s]
+Epoch 1927/4000: 100%|██████████| 10/10 [00:00<00:00, 14.92it/s]
+Epoch 1927/4000: 100%|██████████| 10/10 [00:01<00:00,  9.21it/s]
+Learning rate updated: 0.00014989025404881537
+epoch: 1926, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.362592, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1928/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1928/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 1928/4000:  40%|████      | 4/10 [00:00<00:00,  6.59it/s]
+Epoch 1928/4000:  70%|███████   | 7/10 [00:00<00:00, 10.52it/s]
+Epoch 1928/4000: 100%|██████████| 10/10 [00:01<00:00, 13.79it/s]
+Epoch 1928/4000: 100%|██████████| 10/10 [00:01<00:00,  8.79it/s]
+epoch: 1927, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.360812, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1929/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1929/4000:  10%|█         | 1/10 [00:00<00:05,  1.76it/s]
+Epoch 1929/4000:  40%|████      | 4/10 [00:00<00:00,  6.96it/s]
+Epoch 1929/4000:  70%|███████   | 7/10 [00:00<00:00, 11.60it/s]
+Epoch 1929/4000: 100%|██████████| 10/10 [00:00<00:00, 15.25it/s]
+Epoch 1929/4000: 100%|██████████| 10/10 [00:01<00:00,  9.45it/s]
+epoch: 1928, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.364184, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1930/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1930/4000:  10%|█         | 1/10 [00:00<00:06,  1.50it/s]
+Epoch 1930/4000:  40%|████      | 4/10 [00:00<00:00,  6.10it/s]
+Epoch 1930/4000:  70%|███████   | 7/10 [00:00<00:00, 10.12it/s]
+Epoch 1930/4000: 100%|██████████| 10/10 [00:01<00:00, 13.32it/s]
+Epoch 1930/4000: 100%|██████████| 10/10 [00:01<00:00,  8.28it/s]
+epoch: 1929, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.364027, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1931/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1931/4000:  10%|█         | 1/10 [00:00<00:04,  1.80it/s]
+Epoch 1931/4000:  30%|███       | 3/10 [00:00<00:01,  5.52it/s]
+Epoch 1931/4000:  60%|██████    | 6/10 [00:00<00:00, 10.21it/s]
+Epoch 1931/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.73it/s]
+Epoch 1931/4000: 100%|██████████| 10/10 [00:01<00:00,  9.13it/s]
+epoch: 1930, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.360662, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1932/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1932/4000:  10%|█         | 1/10 [00:00<00:05,  1.76it/s]
+Epoch 1932/4000:  40%|████      | 4/10 [00:00<00:00,  6.92it/s]
+Epoch 1932/4000:  70%|███████   | 7/10 [00:00<00:00, 11.46it/s]
+Epoch 1932/4000: 100%|██████████| 10/10 [00:00<00:00, 15.04it/s]
+Epoch 1932/4000: 100%|██████████| 10/10 [00:01<00:00,  9.31it/s]
+epoch: 1931, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.361646, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1933/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1933/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
+Epoch 1933/4000:  40%|████      | 4/10 [00:00<00:00,  6.88it/s]
+Epoch 1933/4000:  70%|███████   | 7/10 [00:00<00:00, 10.86it/s]
+Epoch 1933/4000: 100%|██████████| 10/10 [00:00<00:00, 14.05it/s]
+Epoch 1933/4000: 100%|██████████| 10/10 [00:01<00:00,  8.93it/s]
+epoch: 1932, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.360182, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1934/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1934/4000:  10%|█         | 1/10 [00:00<00:05,  1.73it/s]
+Epoch 1934/4000:  40%|████      | 4/10 [00:00<00:00,  6.81it/s]
+Epoch 1934/4000:  70%|███████   | 7/10 [00:00<00:00, 11.21it/s]
+Epoch 1934/4000: 100%|██████████| 10/10 [00:00<00:00, 14.39it/s]
+Epoch 1934/4000: 100%|██████████| 10/10 [00:01<00:00,  9.15it/s]
+epoch: 1933, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.361020, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1935/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1935/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 1935/4000:  30%|███       | 3/10 [00:00<00:01,  5.34it/s]
+Epoch 1935/4000:  60%|██████    | 6/10 [00:00<00:00, 10.28it/s]
+Epoch 1935/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.68it/s]
+Epoch 1935/4000: 100%|██████████| 10/10 [00:01<00:00,  8.88it/s]
+epoch: 1934, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.361604, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1936/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1936/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 1936/4000:  30%|███       | 3/10 [00:00<00:01,  5.11it/s]
+Epoch 1936/4000:  60%|██████    | 6/10 [00:00<00:00,  9.69it/s]
+Epoch 1936/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.51it/s]
+Epoch 1936/4000: 100%|██████████| 10/10 [00:01<00:00,  8.76it/s]
+epoch: 1935, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.360349, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1937/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1937/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 1937/4000:  30%|███       | 3/10 [00:00<00:01,  5.51it/s]
+Epoch 1937/4000:  60%|██████    | 6/10 [00:00<00:00, 10.49it/s]
+Epoch 1937/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.46it/s]
+Epoch 1937/4000: 100%|██████████| 10/10 [00:01<00:00,  9.42it/s]
+epoch: 1936, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.359994, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1938/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1938/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 1938/4000:  30%|███       | 3/10 [00:00<00:01,  5.12it/s]
+Epoch 1938/4000:  60%|██████    | 6/10 [00:00<00:00,  9.62it/s]
+Epoch 1938/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.42it/s]
+Epoch 1938/4000: 100%|██████████| 10/10 [00:01<00:00,  8.73it/s]
+Learning rate updated: 0.00014239574134637458
+epoch: 1937, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.359241, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1939/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1939/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 1939/4000:  40%|████      | 4/10 [00:00<00:00,  6.82it/s]
+Epoch 1939/4000:  70%|███████   | 7/10 [00:00<00:00, 11.51it/s]
+Epoch 1939/4000: 100%|██████████| 10/10 [00:00<00:00, 14.59it/s]
+Epoch 1939/4000: 100%|██████████| 10/10 [00:01<00:00,  9.20it/s]
+epoch: 1938, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.357079, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1940/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1940/4000:  10%|█         | 1/10 [00:00<00:05,  1.79it/s]
+Epoch 1940/4000:  40%|████      | 4/10 [00:00<00:00,  6.95it/s]
+Epoch 1940/4000:  70%|███████   | 7/10 [00:00<00:00, 11.31it/s]
+Epoch 1940/4000: 100%|██████████| 10/10 [00:00<00:00, 14.60it/s]
+Epoch 1940/4000: 100%|██████████| 10/10 [00:01<00:00,  9.25it/s]
+epoch: 1939, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.358427, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1941/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1941/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1941/4000:  40%|████      | 4/10 [00:00<00:00,  6.51it/s]
+Epoch 1941/4000:  70%|███████   | 7/10 [00:00<00:00, 10.74it/s]
+Epoch 1941/4000: 100%|██████████| 10/10 [00:01<00:00, 13.80it/s]
+Epoch 1941/4000: 100%|██████████| 10/10 [00:01<00:00,  8.84it/s]
+epoch: 1940, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.360097, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1942/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1942/4000:  10%|█         | 1/10 [00:00<00:05,  1.64it/s]
+Epoch 1942/4000:  30%|███       | 3/10 [00:00<00:01,  5.09it/s]
+Epoch 1942/4000:  60%|██████    | 6/10 [00:00<00:00,  9.91it/s]
+Epoch 1942/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.53it/s]
+Epoch 1942/4000: 100%|██████████| 10/10 [00:01<00:00,  8.78it/s]
+epoch: 1941, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.359696, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1943/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1943/4000:  10%|█         | 1/10 [00:00<00:05,  1.76it/s]
+Epoch 1943/4000:  30%|███       | 3/10 [00:00<00:01,  5.39it/s]
+Epoch 1943/4000:  60%|██████    | 6/10 [00:00<00:00,  9.98it/s]
+Epoch 1943/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.23it/s]
+Epoch 1943/4000: 100%|██████████| 10/10 [00:01<00:00,  8.82it/s]
+epoch: 1942, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.358069, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1944/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1944/4000:  10%|█         | 1/10 [00:00<00:05,  1.73it/s]
+Epoch 1944/4000:  40%|████      | 4/10 [00:00<00:00,  6.81it/s]
+Epoch 1944/4000:  70%|███████   | 7/10 [00:00<00:00, 10.96it/s]
+Epoch 1944/4000: 100%|██████████| 10/10 [00:00<00:00, 14.20it/s]
+Epoch 1944/4000: 100%|██████████| 10/10 [00:01<00:00,  9.06it/s]
+epoch: 1943, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.359331, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1945/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1945/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 1945/4000:  40%|████      | 4/10 [00:00<00:00,  6.72it/s]
+Epoch 1945/4000:  70%|███████   | 7/10 [00:00<00:00, 11.01it/s]
+Epoch 1945/4000: 100%|██████████| 10/10 [00:00<00:00, 14.47it/s]
+Epoch 1945/4000: 100%|██████████| 10/10 [00:01<00:00,  9.08it/s]
+epoch: 1944, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.354634, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1946/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1946/4000:  10%|█         | 1/10 [00:00<00:05,  1.69it/s]
+Epoch 1946/4000:  30%|███       | 3/10 [00:00<00:01,  5.25it/s]
+Epoch 1946/4000:  60%|██████    | 6/10 [00:00<00:00,  9.75it/s]
+Epoch 1946/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.03it/s]
+Epoch 1946/4000: 100%|██████████| 10/10 [00:01<00:00,  8.71it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1947/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1947/4000:  10%|█         | 1/10 [00:00<00:05,  1.73it/s]
+Epoch 1947/4000:  30%|███       | 3/10 [00:00<00:01,  5.32it/s]
+Epoch 1947/4000:  60%|██████    | 6/10 [00:00<00:00, 10.37it/s]
+Epoch 1947/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.90it/s]
+Epoch 1947/4000: 100%|██████████| 10/10 [00:01<00:00,  8.89it/s]
+epoch: 1946, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.360568, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1948/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1948/4000:  10%|█         | 1/10 [00:00<00:05,  1.58it/s]
+Epoch 1948/4000:  40%|████      | 4/10 [00:00<00:00,  6.37it/s]
+Epoch 1948/4000:  70%|███████   | 7/10 [00:00<00:00, 10.58it/s]
+Epoch 1948/4000: 100%|██████████| 10/10 [00:01<00:00, 14.02it/s]
+Epoch 1948/4000: 100%|██████████| 10/10 [00:01<00:00,  8.72it/s]
+epoch: 1947, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.360551, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1949/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1949/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 1949/4000:  30%|███       | 3/10 [00:00<00:01,  5.36it/s]
+Epoch 1949/4000:  60%|██████    | 6/10 [00:00<00:00, 10.05it/s]
+Epoch 1949/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.54it/s]
+Epoch 1949/4000: 100%|██████████| 10/10 [00:01<00:00,  9.01it/s]
+Learning rate updated: 0.00013527595427905584
+epoch: 1948, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.360123, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1950/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1950/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 1950/4000:  40%|████      | 4/10 [00:00<00:00,  6.70it/s]
+Epoch 1950/4000:  70%|███████   | 7/10 [00:00<00:00, 11.09it/s]
+Epoch 1950/4000: 100%|██████████| 10/10 [00:00<00:00, 14.64it/s]
+Epoch 1950/4000: 100%|██████████| 10/10 [00:01<00:00,  9.15it/s]
+epoch: 1949, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.358677, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1951/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1951/4000:  10%|█         | 1/10 [00:00<00:05,  1.51it/s]
+Epoch 1951/4000:  30%|███       | 3/10 [00:00<00:01,  4.76it/s]
+Epoch 1951/4000:  60%|██████    | 6/10 [00:00<00:00,  9.26it/s]
+Epoch 1951/4000:  90%|█████████ | 9/10 [00:01<00:00, 12.82it/s]
+Epoch 1951/4000: 100%|██████████| 10/10 [00:01<00:00,  8.20it/s]
+epoch: 1950, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.356794, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1952/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1952/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 1952/4000:  30%|███       | 3/10 [00:00<00:01,  5.26it/s]
+Epoch 1952/4000:  60%|██████    | 6/10 [00:00<00:00,  9.98it/s]
+Epoch 1952/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.81it/s]
+Epoch 1952/4000: 100%|██████████| 10/10 [00:01<00:00,  9.02it/s]
+epoch: 1951, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.357727, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1953/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1953/4000:  10%|█         | 1/10 [00:00<00:05,  1.52it/s]
+Epoch 1953/4000:  40%|████      | 4/10 [00:00<00:00,  6.14it/s]
+Epoch 1953/4000:  70%|███████   | 7/10 [00:00<00:00, 10.50it/s]
+Epoch 1953/4000: 100%|██████████| 10/10 [00:01<00:00, 14.09it/s]
+Epoch 1953/4000: 100%|██████████| 10/10 [00:01<00:00,  8.65it/s]
+epoch: 1952, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.356472, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1954/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1954/4000:  10%|█         | 1/10 [00:00<00:05,  1.60it/s]
+Epoch 1954/4000:  40%|████      | 4/10 [00:00<00:00,  6.41it/s]
+Epoch 1954/4000:  70%|███████   | 7/10 [00:00<00:00, 10.41it/s]
+Epoch 1954/4000: 100%|██████████| 10/10 [00:01<00:00, 13.70it/s]
+Epoch 1954/4000: 100%|██████████| 10/10 [00:01<00:00,  8.58it/s]
+epoch: 1953, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.355686, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1955/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1955/4000:  10%|█         | 1/10 [00:00<00:05,  1.69it/s]
+Epoch 1955/4000:  30%|███       | 3/10 [00:00<00:01,  5.15it/s]
+Epoch 1955/4000:  60%|██████    | 6/10 [00:00<00:00,  9.70it/s]
+Epoch 1955/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.51it/s]
+Epoch 1955/4000: 100%|██████████| 10/10 [00:01<00:00,  8.76it/s]
+epoch: 1954, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.357538, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1956/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1956/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1956/4000:  30%|███       | 3/10 [00:00<00:01,  5.14it/s]
+Epoch 1956/4000:  60%|██████    | 6/10 [00:00<00:00, 10.16it/s]
+Epoch 1956/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.17it/s]
+Epoch 1956/4000: 100%|██████████| 10/10 [00:01<00:00,  8.92it/s]
+epoch: 1955, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.356799, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1957/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1957/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1957/4000:  30%|███       | 3/10 [00:00<00:01,  5.24it/s]
+Epoch 1957/4000:  60%|██████    | 6/10 [00:00<00:00, 10.03it/s]
+Epoch 1957/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.14it/s]
+Epoch 1957/4000: 100%|██████████| 10/10 [00:01<00:00,  9.08it/s]
+epoch: 1956, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.355578, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1958/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1958/4000:  10%|█         | 1/10 [00:00<00:05,  1.73it/s]
+Epoch 1958/4000:  40%|████      | 4/10 [00:00<00:00,  6.72it/s]
+Epoch 1958/4000:  70%|███████   | 7/10 [00:00<00:00, 11.11it/s]
+Epoch 1958/4000: 100%|██████████| 10/10 [00:00<00:00, 14.53it/s]
+Epoch 1958/4000: 100%|██████████| 10/10 [00:01<00:00,  9.15it/s]
+epoch: 1957, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000001, Train KL:3.367574, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1959/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1959/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 1959/4000:  40%|████      | 4/10 [00:00<00:00,  6.74it/s]
+Epoch 1959/4000:  70%|███████   | 7/10 [00:00<00:00, 11.08it/s]
+Epoch 1959/4000: 100%|██████████| 10/10 [00:00<00:00, 14.67it/s]
+Epoch 1959/4000: 100%|██████████| 10/10 [00:01<00:00,  8.95it/s]
+epoch: 1958, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.431020, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1960/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1960/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1960/4000:  40%|████      | 4/10 [00:00<00:00,  6.71it/s]
+Epoch 1960/4000:  70%|███████   | 7/10 [00:00<00:00, 10.91it/s]
+Epoch 1960/4000: 100%|██████████| 10/10 [00:00<00:00, 14.13it/s]
+Epoch 1960/4000: 100%|██████████| 10/10 [00:01<00:00,  8.61it/s]
+epoch: 1959, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.424289, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1961/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1961/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 1961/4000:  30%|███       | 3/10 [00:00<00:01,  5.27it/s]
+Epoch 1961/4000:  50%|█████     | 5/10 [00:00<00:00,  8.42it/s]
+Epoch 1961/4000:  80%|████████  | 8/10 [00:00<00:00, 12.30it/s]
+Epoch 1961/4000: 100%|██████████| 10/10 [00:01<00:00,  8.66it/s]
+epoch: 1960, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.399699, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1962/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1962/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1962/4000:  40%|████      | 4/10 [00:00<00:00,  6.61it/s]
+Epoch 1962/4000:  70%|███████   | 7/10 [00:00<00:00, 10.91it/s]
+Epoch 1962/4000: 100%|██████████| 10/10 [00:00<00:00, 14.65it/s]
+Epoch 1962/4000: 100%|██████████| 10/10 [00:01<00:00,  9.09it/s]
+epoch: 1961, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.393322, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1963/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1963/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 1963/4000:  40%|████      | 4/10 [00:00<00:00,  6.69it/s]
+Epoch 1963/4000:  70%|███████   | 7/10 [00:00<00:00, 10.87it/s]
+Epoch 1963/4000: 100%|██████████| 10/10 [00:00<00:00, 14.09it/s]
+Epoch 1963/4000: 100%|██████████| 10/10 [00:01<00:00,  8.99it/s]
+epoch: 1962, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.391804, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1964/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1964/4000:  10%|█         | 1/10 [00:00<00:05,  1.62it/s]
+Epoch 1964/4000:  40%|████      | 4/10 [00:00<00:00,  6.45it/s]
+Epoch 1964/4000:  70%|███████   | 7/10 [00:00<00:00, 10.70it/s]
+Epoch 1964/4000:  90%|█████████ | 9/10 [00:00<00:00, 12.61it/s]
+Epoch 1964/4000: 100%|██████████| 10/10 [00:01<00:00,  8.59it/s]
+epoch: 1963, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.382737, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1965/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1965/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 1965/4000:  40%|████      | 4/10 [00:00<00:00,  6.69it/s]
+Epoch 1965/4000:  70%|███████   | 7/10 [00:00<00:00, 10.76it/s]
+Epoch 1965/4000: 100%|██████████| 10/10 [00:00<00:00, 13.89it/s]
+Epoch 1965/4000: 100%|██████████| 10/10 [00:01<00:00,  8.88it/s]
+epoch: 1964, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.380122, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1966/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1966/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 1966/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 1966/4000:  70%|███████   | 7/10 [00:00<00:00, 11.21it/s]
+Epoch 1966/4000: 100%|██████████| 10/10 [00:00<00:00, 14.26it/s]
+Epoch 1966/4000: 100%|██████████| 10/10 [00:01<00:00,  9.03it/s]
+epoch: 1965, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.383014, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1967/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1967/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1967/4000:  40%|████      | 4/10 [00:00<00:00,  6.88it/s]
+Epoch 1967/4000:  70%|███████   | 7/10 [00:00<00:00, 11.43it/s]
+Epoch 1967/4000: 100%|██████████| 10/10 [00:00<00:00, 15.14it/s]
+Epoch 1967/4000: 100%|██████████| 10/10 [00:01<00:00,  9.29it/s]
+epoch: 1966, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.380071, Val MSE:0.000009, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1968/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1968/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1968/4000:  30%|███       | 3/10 [00:00<00:01,  5.25it/s]
+Epoch 1968/4000:  50%|█████     | 5/10 [00:00<00:00,  8.31it/s]
+Epoch 1968/4000:  80%|████████  | 8/10 [00:00<00:00, 12.54it/s]
+Epoch 1968/4000: 100%|██████████| 10/10 [00:01<00:00,  8.70it/s]
+epoch: 1967, beta = 0.000008, Train MSE: 0.000010, Train CE:0.000000, Train KL:3.376042, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1969/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1969/4000:  10%|█         | 1/10 [00:00<00:05,  1.61it/s]
+Epoch 1969/4000:  40%|████      | 4/10 [00:00<00:00,  6.45it/s]
+Epoch 1969/4000:  70%|███████   | 7/10 [00:00<00:00, 10.62it/s]
+Epoch 1969/4000: 100%|██████████| 10/10 [00:01<00:00, 13.74it/s]
+Epoch 1969/4000: 100%|██████████| 10/10 [00:01<00:00,  8.70it/s]
+epoch: 1968, beta = 0.000008, Train MSE: 0.000006, Train CE:0.000000, Train KL:3.376611, Val MSE:0.000005, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1970/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1970/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 1970/4000:  40%|████      | 4/10 [00:00<00:00,  7.21it/s]
+Epoch 1970/4000:  70%|███████   | 7/10 [00:00<00:00, 12.12it/s]
+Epoch 1970/4000: 100%|██████████| 10/10 [00:00<00:00, 15.43it/s]
+Epoch 1970/4000: 100%|██████████| 10/10 [00:01<00:00,  9.62it/s]
+epoch: 1969, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.371117, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1971/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1971/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 1971/4000:  40%|████      | 4/10 [00:00<00:00,  6.72it/s]
+Epoch 1971/4000:  70%|███████   | 7/10 [00:00<00:00, 10.95it/s]
+Epoch 1971/4000: 100%|██████████| 10/10 [00:00<00:00, 13.81it/s]
+Epoch 1971/4000: 100%|██████████| 10/10 [00:01<00:00,  8.86it/s]
+epoch: 1970, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.368936, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1972/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1972/4000:  10%|█         | 1/10 [00:00<00:04,  1.80it/s]
+Epoch 1972/4000:  40%|████      | 4/10 [00:00<00:00,  7.16it/s]
+Epoch 1972/4000:  70%|███████   | 7/10 [00:00<00:00, 12.06it/s]
+Epoch 1972/4000: 100%|██████████| 10/10 [00:00<00:00, 16.00it/s]
+Epoch 1972/4000: 100%|██████████| 10/10 [00:01<00:00,  9.76it/s]
+Learning rate updated: 0.00012851215656510304
+epoch: 1971, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.371142, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1973/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1973/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1973/4000:  40%|████      | 4/10 [00:00<00:00,  6.94it/s]
+Epoch 1973/4000:  70%|███████   | 7/10 [00:00<00:00, 11.69it/s]
+Epoch 1973/4000: 100%|██████████| 10/10 [00:00<00:00, 15.48it/s]
+Epoch 1973/4000: 100%|██████████| 10/10 [00:01<00:00,  9.41it/s]
+epoch: 1972, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.367943, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1974/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1974/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 1974/4000:  30%|███       | 3/10 [00:00<00:01,  5.22it/s]
+Epoch 1974/4000:  60%|██████    | 6/10 [00:00<00:00,  9.84it/s]
+Epoch 1974/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.40it/s]
+Epoch 1974/4000: 100%|██████████| 10/10 [00:01<00:00,  8.62it/s]
+epoch: 1973, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.368559, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1975/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1975/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 1975/4000:  40%|████      | 4/10 [00:00<00:00,  7.04it/s]
+Epoch 1975/4000:  70%|███████   | 7/10 [00:00<00:00, 11.68it/s]
+Epoch 1975/4000: 100%|██████████| 10/10 [00:00<00:00, 15.56it/s]
+Epoch 1975/4000: 100%|██████████| 10/10 [00:01<00:00,  9.61it/s]
+epoch: 1974, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.365873, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1976/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1976/4000:  10%|█         | 1/10 [00:00<00:04,  1.83it/s]
+Epoch 1976/4000:  40%|████      | 4/10 [00:00<00:00,  7.28it/s]
+Epoch 1976/4000:  70%|███████   | 7/10 [00:00<00:00, 12.06it/s]
+Epoch 1976/4000: 100%|██████████| 10/10 [00:00<00:00, 15.27it/s]
+Epoch 1976/4000: 100%|██████████| 10/10 [00:01<00:00,  9.66it/s]
+epoch: 1975, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.371171, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1977/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1977/4000:  10%|█         | 1/10 [00:00<00:05,  1.79it/s]
+Epoch 1977/4000:  40%|████      | 4/10 [00:00<00:00,  7.11it/s]
+Epoch 1977/4000:  70%|███████   | 7/10 [00:00<00:00, 11.63it/s]
+Epoch 1977/4000: 100%|██████████| 10/10 [00:00<00:00, 14.88it/s]
+Epoch 1977/4000: 100%|██████████| 10/10 [00:01<00:00,  9.04it/s]
+epoch: 1976, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.366969, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1978/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1978/4000:  10%|█         | 1/10 [00:00<00:05,  1.64it/s]
+Epoch 1978/4000:  40%|████      | 4/10 [00:00<00:00,  6.65it/s]
+Epoch 1978/4000:  70%|███████   | 7/10 [00:00<00:00, 11.11it/s]
+Epoch 1978/4000: 100%|██████████| 10/10 [00:00<00:00, 14.78it/s]
+Epoch 1978/4000: 100%|██████████| 10/10 [00:01<00:00,  9.10it/s]
+epoch: 1977, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.364511, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1979/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1979/4000:  10%|█         | 1/10 [00:00<00:05,  1.75it/s]
+Epoch 1979/4000:  40%|████      | 4/10 [00:00<00:00,  6.85it/s]
+Epoch 1979/4000:  70%|███████   | 7/10 [00:00<00:00, 10.83it/s]
+Epoch 1979/4000:  90%|█████████ | 9/10 [00:00<00:00, 12.68it/s]
+Epoch 1979/4000: 100%|██████████| 10/10 [00:01<00:00,  8.85it/s]
+epoch: 1978, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.363427, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1980/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1980/4000:  10%|█         | 1/10 [00:00<00:05,  1.51it/s]
+Epoch 1980/4000:  40%|████      | 4/10 [00:00<00:00,  6.11it/s]
+Epoch 1980/4000:  70%|███████   | 7/10 [00:00<00:00, 10.20it/s]
+Epoch 1980/4000: 100%|██████████| 10/10 [00:01<00:00, 13.45it/s]
+Epoch 1980/4000: 100%|██████████| 10/10 [00:01<00:00,  8.42it/s]
+epoch: 1979, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.364789, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1981/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1981/4000:  10%|█         | 1/10 [00:00<00:04,  1.80it/s]
+Epoch 1981/4000:  40%|████      | 4/10 [00:00<00:00,  7.10it/s]
+Epoch 1981/4000:  70%|███████   | 7/10 [00:00<00:00, 11.19it/s]
+Epoch 1981/4000: 100%|██████████| 10/10 [00:00<00:00, 14.92it/s]
+Epoch 1981/4000: 100%|██████████| 10/10 [00:01<00:00,  9.37it/s]
+epoch: 1980, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.365693, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1982/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1982/4000:  10%|█         | 1/10 [00:00<00:05,  1.75it/s]
+Epoch 1982/4000:  40%|████      | 4/10 [00:00<00:00,  6.86it/s]
+Epoch 1982/4000:  70%|███████   | 7/10 [00:00<00:00, 10.86it/s]
+Epoch 1982/4000: 100%|██████████| 10/10 [00:00<00:00, 13.69it/s]
+Epoch 1982/4000: 100%|██████████| 10/10 [00:01<00:00,  8.91it/s]
+epoch: 1981, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.365286, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1983/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1983/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 1983/4000:  40%|████      | 4/10 [00:00<00:00,  6.79it/s]
+Epoch 1983/4000:  70%|███████   | 7/10 [00:00<00:00, 11.45it/s]
+Epoch 1983/4000: 100%|██████████| 10/10 [00:00<00:00, 14.70it/s]
+Epoch 1983/4000: 100%|██████████| 10/10 [00:01<00:00,  9.07it/s]
+Learning rate updated: 0.00012208654873684788
+epoch: 1982, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.366912, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1984/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1984/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 1984/4000:  40%|████      | 4/10 [00:00<00:00,  6.90it/s]
+Epoch 1984/4000:  70%|███████   | 7/10 [00:00<00:00, 11.32it/s]
+Epoch 1984/4000:  90%|█████████ | 9/10 [00:00<00:00, 12.99it/s]
+Epoch 1984/4000: 100%|██████████| 10/10 [00:01<00:00,  8.96it/s]
+epoch: 1983, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.364804, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1985/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1985/4000:  10%|█         | 1/10 [00:00<00:05,  1.73it/s]
+Epoch 1985/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 1985/4000:  70%|███████   | 7/10 [00:00<00:00, 11.15it/s]
+Epoch 1985/4000: 100%|██████████| 10/10 [00:00<00:00, 14.65it/s]
+Epoch 1985/4000: 100%|██████████| 10/10 [00:01<00:00,  9.21it/s]
+epoch: 1984, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.361710, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1986/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1986/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 1986/4000:  30%|███       | 3/10 [00:00<00:01,  5.31it/s]
+Epoch 1986/4000:  60%|██████    | 6/10 [00:00<00:00,  9.98it/s]
+Epoch 1986/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.59it/s]
+Epoch 1986/4000: 100%|██████████| 10/10 [00:01<00:00,  8.94it/s]
+epoch: 1985, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.361931, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1987/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1987/4000:  10%|█         | 1/10 [00:00<00:05,  1.61it/s]
+Epoch 1987/4000:  40%|████      | 4/10 [00:00<00:00,  6.57it/s]
+Epoch 1987/4000:  70%|███████   | 7/10 [00:00<00:00, 10.80it/s]
+Epoch 1987/4000: 100%|██████████| 10/10 [00:01<00:00, 13.58it/s]
+Epoch 1987/4000: 100%|██████████| 10/10 [00:01<00:00,  8.70it/s]
+epoch: 1986, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.359756, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1988/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1988/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
+Epoch 1988/4000:  40%|████      | 4/10 [00:00<00:00,  7.02it/s]
+Epoch 1988/4000:  70%|███████   | 7/10 [00:00<00:00, 11.55it/s]
+Epoch 1988/4000: 100%|██████████| 10/10 [00:00<00:00, 15.00it/s]
+Epoch 1988/4000: 100%|██████████| 10/10 [00:01<00:00,  9.39it/s]
+epoch: 1987, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.360915, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1989/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1989/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 1989/4000:  40%|████      | 4/10 [00:00<00:00,  6.79it/s]
+Epoch 1989/4000:  70%|███████   | 7/10 [00:00<00:00, 10.60it/s]
+Epoch 1989/4000: 100%|██████████| 10/10 [00:00<00:00, 14.19it/s]
+Epoch 1989/4000: 100%|██████████| 10/10 [00:01<00:00,  8.92it/s]
+epoch: 1988, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.361644, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1990/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1990/4000:  10%|█         | 1/10 [00:00<00:05,  1.73it/s]
+Epoch 1990/4000:  40%|████      | 4/10 [00:00<00:00,  6.76it/s]
+Epoch 1990/4000:  70%|███████   | 7/10 [00:00<00:00, 11.27it/s]
+Epoch 1990/4000: 100%|██████████| 10/10 [00:00<00:00, 14.47it/s]
+Epoch 1990/4000: 100%|██████████| 10/10 [00:01<00:00,  9.16it/s]
+epoch: 1989, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.359781, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1991/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1991/4000:  10%|█         | 1/10 [00:00<00:05,  1.58it/s]
+Epoch 1991/4000:  40%|████      | 4/10 [00:00<00:00,  6.46it/s]
+Epoch 1991/4000:  70%|███████   | 7/10 [00:00<00:00, 11.01it/s]
+Epoch 1991/4000: 100%|██████████| 10/10 [00:00<00:00, 14.85it/s]
+Epoch 1991/4000: 100%|██████████| 10/10 [00:01<00:00,  9.02it/s]
+epoch: 1990, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.359536, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1992/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1992/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
+Epoch 1992/4000:  40%|████      | 4/10 [00:00<00:00,  7.00it/s]
+Epoch 1992/4000:  70%|███████   | 7/10 [00:00<00:00, 11.31it/s]
+Epoch 1992/4000: 100%|██████████| 10/10 [00:00<00:00, 14.42it/s]
+Epoch 1992/4000: 100%|██████████| 10/10 [00:01<00:00,  9.18it/s]
+epoch: 1991, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.357702, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1993/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1993/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 1993/4000:  40%|████      | 4/10 [00:00<00:00,  6.90it/s]
+Epoch 1993/4000:  70%|███████   | 7/10 [00:00<00:00, 11.22it/s]
+Epoch 1993/4000: 100%|██████████| 10/10 [00:00<00:00, 14.56it/s]
+Epoch 1993/4000: 100%|██████████| 10/10 [00:01<00:00,  9.21it/s]
+epoch: 1992, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.358893, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1994/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1994/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1994/4000:  40%|████      | 4/10 [00:00<00:00,  6.70it/s]
+Epoch 1994/4000:  70%|███████   | 7/10 [00:00<00:00, 11.02it/s]
+Epoch 1994/4000: 100%|██████████| 10/10 [00:00<00:00, 14.40it/s]
+Epoch 1994/4000: 100%|██████████| 10/10 [00:01<00:00,  9.05it/s]
+Learning rate updated: 0.00011598222130000548
+epoch: 1993, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.359554, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1995/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1995/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
+Epoch 1995/4000:  30%|███       | 3/10 [00:00<00:01,  5.41it/s]
+Epoch 1995/4000:  60%|██████    | 6/10 [00:00<00:00,  9.85it/s]
+Epoch 1995/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.07it/s]
+Epoch 1995/4000: 100%|██████████| 10/10 [00:01<00:00,  8.68it/s]
+
+  0%|          | 0/10 [00:00<?, ?it/s]epoch: 1994, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.358668, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+Epoch 1996/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1996/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 1996/4000:  40%|████      | 4/10 [00:00<00:00,  6.79it/s]
+Epoch 1996/4000:  70%|███████   | 7/10 [00:00<00:00, 11.42it/s]
+Epoch 1996/4000: 100%|██████████| 10/10 [00:00<00:00, 15.00it/s]
+Epoch 1996/4000: 100%|██████████| 10/10 [00:01<00:00,  9.31it/s]
+epoch: 1995, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.358410, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1997/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1997/4000:  10%|█         | 1/10 [00:00<00:05,  1.64it/s]
+Epoch 1997/4000:  30%|███       | 3/10 [00:00<00:01,  4.95it/s]
+Epoch 1997/4000:  60%|██████    | 6/10 [00:00<00:00,  9.42it/s]
+Epoch 1997/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.33it/s]
+Epoch 1997/4000: 100%|██████████| 10/10 [00:01<00:00,  8.66it/s]
+epoch: 1996, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.357866, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1998/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1998/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 1998/4000:  40%|████      | 4/10 [00:00<00:00,  6.50it/s]
+Epoch 1998/4000:  70%|███████   | 7/10 [00:00<00:00, 10.55it/s]
+Epoch 1998/4000: 100%|██████████| 10/10 [00:01<00:00, 13.63it/s]
+Epoch 1998/4000: 100%|██████████| 10/10 [00:01<00:00,  8.73it/s]
+epoch: 1997, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.356677, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1999/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1999/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 1999/4000:  40%|████      | 4/10 [00:00<00:00,  6.78it/s]
+Epoch 1999/4000:  70%|███████   | 7/10 [00:00<00:00, 11.43it/s]
+Epoch 1999/4000: 100%|██████████| 10/10 [00:00<00:00, 14.75it/s]
+Epoch 1999/4000: 100%|██████████| 10/10 [00:01<00:00,  9.23it/s]
+epoch: 1998, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.357176, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2000/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2000/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 2000/4000:  40%|████      | 4/10 [00:00<00:00,  6.74it/s]
+Epoch 2000/4000:  70%|███████   | 7/10 [00:00<00:00, 10.92it/s]
+Epoch 2000/4000: 100%|██████████| 10/10 [00:00<00:00, 13.87it/s]
+Epoch 2000/4000: 100%|██████████| 10/10 [00:01<00:00,  8.83it/s]
+epoch: 1999, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.357164, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2001/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2001/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 2001/4000:  40%|████      | 4/10 [00:00<00:00,  6.56it/s]
+Epoch 2001/4000:  70%|███████   | 7/10 [00:00<00:00, 11.06it/s]
+Epoch 2001/4000: 100%|██████████| 10/10 [00:00<00:00, 14.21it/s]
+Epoch 2001/4000: 100%|██████████| 10/10 [00:01<00:00,  8.95it/s]
+epoch: 2000, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.357058, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2002/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2002/4000:  10%|█         | 1/10 [00:00<00:06,  1.41it/s]
+Epoch 2002/4000:  40%|████      | 4/10 [00:00<00:01,  5.87it/s]
+Epoch 2002/4000:  70%|███████   | 7/10 [00:00<00:00, 10.06it/s]
+Epoch 2002/4000: 100%|██████████| 10/10 [00:01<00:00, 13.50it/s]
+Epoch 2002/4000: 100%|██████████| 10/10 [00:01<00:00,  8.27it/s]
+epoch: 2001, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.356558, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2003/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2003/4000:  10%|█         | 1/10 [00:00<00:05,  1.66it/s]
+Epoch 2003/4000:  30%|███       | 3/10 [00:00<00:01,  5.18it/s]
+Epoch 2003/4000:  60%|██████    | 6/10 [00:00<00:00,  9.68it/s]
+Epoch 2003/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.09it/s]
+Epoch 2003/4000: 100%|██████████| 10/10 [00:01<00:00,  8.62it/s]
+epoch: 2002, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.356339, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2004/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2004/4000:  10%|█         | 1/10 [00:00<00:05,  1.69it/s]
+Epoch 2004/4000:  40%|████      | 4/10 [00:00<00:00,  6.53it/s]
+Epoch 2004/4000:  70%|███████   | 7/10 [00:00<00:00, 10.88it/s]
+Epoch 2004/4000: 100%|██████████| 10/10 [00:00<00:00, 13.92it/s]
+Epoch 2004/4000: 100%|██████████| 10/10 [00:01<00:00,  8.91it/s]
+epoch: 2003, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.357101, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2005/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2005/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 2005/4000:  40%|████      | 4/10 [00:00<00:00,  6.81it/s]
+Epoch 2005/4000:  70%|███████   | 7/10 [00:00<00:00, 11.39it/s]
+Epoch 2005/4000: 100%|██████████| 10/10 [00:00<00:00, 14.72it/s]
+Epoch 2005/4000: 100%|██████████| 10/10 [00:01<00:00,  9.23it/s]
+Learning rate updated: 0.00011018311023500519
+epoch: 2004, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.355195, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2006/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2006/4000:  10%|█         | 1/10 [00:00<00:05,  1.64it/s]
+Epoch 2006/4000:  40%|████      | 4/10 [00:00<00:00,  6.60it/s]
+Epoch 2006/4000:  70%|███████   | 7/10 [00:00<00:00, 11.04it/s]
+Epoch 2006/4000: 100%|██████████| 10/10 [00:00<00:00, 14.10it/s]
+Epoch 2006/4000: 100%|██████████| 10/10 [00:01<00:00,  8.90it/s]
+epoch: 2005, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.355647, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2007/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2007/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 2007/4000:  40%|████      | 4/10 [00:00<00:00,  6.68it/s]
+Epoch 2007/4000:  70%|███████   | 7/10 [00:00<00:00, 10.92it/s]
+Epoch 2007/4000: 100%|██████████| 10/10 [00:00<00:00, 13.92it/s]
+Epoch 2007/4000: 100%|██████████| 10/10 [00:01<00:00,  8.93it/s]
+epoch: 2006, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.356138, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2008/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2008/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 2008/4000:  30%|███       | 3/10 [00:00<00:01,  5.16it/s]
+Epoch 2008/4000:  60%|██████    | 6/10 [00:00<00:00, 10.14it/s]
+Epoch 2008/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.93it/s]
+Epoch 2008/4000: 100%|██████████| 10/10 [00:01<00:00,  9.00it/s]
+epoch: 2007, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.356913, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2009/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2009/4000:  10%|█         | 1/10 [00:00<00:05,  1.76it/s]
+Epoch 2009/4000:  40%|████      | 4/10 [00:00<00:00,  6.82it/s]
+Epoch 2009/4000:  70%|███████   | 7/10 [00:00<00:00, 10.82it/s]
+Epoch 2009/4000: 100%|██████████| 10/10 [00:00<00:00, 13.86it/s]
+Epoch 2009/4000: 100%|██████████| 10/10 [00:01<00:00,  8.90it/s]
+epoch: 2008, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.353423, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2010/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2010/4000:  10%|█         | 1/10 [00:00<00:05,  1.77it/s]
+Epoch 2010/4000:  40%|████      | 4/10 [00:00<00:00,  7.12it/s]
+Epoch 2010/4000:  70%|███████   | 7/10 [00:00<00:00, 11.78it/s]
+Epoch 2010/4000: 100%|██████████| 10/10 [00:00<00:00, 15.29it/s]
+Epoch 2010/4000: 100%|██████████| 10/10 [00:01<00:00,  9.40it/s]
+epoch: 2009, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.351937, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2011/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2011/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 2011/4000:  40%|████      | 4/10 [00:00<00:00,  6.71it/s]
+Epoch 2011/4000:  70%|███████   | 7/10 [00:00<00:00, 11.26it/s]
+Epoch 2011/4000: 100%|██████████| 10/10 [00:00<00:00, 14.11it/s]
+Epoch 2011/4000: 100%|██████████| 10/10 [00:01<00:00,  8.94it/s]
+epoch: 2010, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.351785, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2012/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2012/4000:  10%|█         | 1/10 [00:00<00:05,  1.66it/s]
+Epoch 2012/4000:  30%|███       | 3/10 [00:00<00:01,  5.10it/s]
+Epoch 2012/4000:  60%|██████    | 6/10 [00:00<00:00,  9.86it/s]
+Epoch 2012/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.63it/s]
+Epoch 2012/4000: 100%|██████████| 10/10 [00:01<00:00,  8.86it/s]
+epoch: 2011, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.355065, Val MSE:0.000004, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2013/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2013/4000:  10%|█         | 1/10 [00:00<00:05,  1.69it/s]
+Epoch 2013/4000:  30%|███       | 3/10 [00:00<00:01,  5.16it/s]
+Epoch 2013/4000:  60%|██████    | 6/10 [00:00<00:00,  9.94it/s]
+Epoch 2013/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.06it/s]
+Epoch 2013/4000: 100%|██████████| 10/10 [00:01<00:00,  9.03it/s]
+epoch: 2012, beta = 0.000008, Train MSE: 0.000004, Train CE:0.000000, Train KL:3.353318, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2014/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2014/4000:  10%|█         | 1/10 [00:00<00:05,  1.77it/s]
+Epoch 2014/4000:  40%|████      | 4/10 [00:00<00:00,  6.72it/s]
+Epoch 2014/4000:  70%|███████   | 7/10 [00:00<00:00, 10.86it/s]
+Epoch 2014/4000: 100%|██████████| 10/10 [00:00<00:00, 14.21it/s]
+Epoch 2014/4000: 100%|██████████| 10/10 [00:01<00:00,  9.08it/s]
+epoch: 2013, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.352098, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2015/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2015/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 2015/4000:  40%|████      | 4/10 [00:00<00:00,  6.69it/s]
+Epoch 2015/4000:  70%|███████   | 7/10 [00:00<00:00, 11.16it/s]
+Epoch 2015/4000: 100%|██████████| 10/10 [00:00<00:00, 14.30it/s]
+Epoch 2015/4000: 100%|██████████| 10/10 [00:01<00:00,  9.06it/s]
+epoch: 2014, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.353407, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2016/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2016/4000:  10%|█         | 1/10 [00:00<00:05,  1.63it/s]
+Epoch 2016/4000:  40%|████      | 4/10 [00:00<00:00,  6.56it/s]
+Epoch 2016/4000:  70%|███████   | 7/10 [00:00<00:00, 11.11it/s]
+Epoch 2016/4000: 100%|██████████| 10/10 [00:00<00:00, 14.52it/s]
+Epoch 2016/4000: 100%|██████████| 10/10 [00:01<00:00,  9.00it/s]
+Learning rate updated: 0.00010467395472325493
+epoch: 2015, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.354416, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2017/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2017/4000:  10%|█         | 1/10 [00:00<00:05,  1.69it/s]
+Epoch 2017/4000:  40%|████      | 4/10 [00:00<00:00,  6.84it/s]
+Epoch 2017/4000:  70%|███████   | 7/10 [00:00<00:00, 11.18it/s]
+Epoch 2017/4000: 100%|██████████| 10/10 [00:00<00:00, 14.69it/s]
+Epoch 2017/4000: 100%|██████████| 10/10 [00:01<00:00,  9.18it/s]
+epoch: 2016, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.352121, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2018/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2018/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 2018/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 2018/4000:  70%|███████   | 7/10 [00:00<00:00, 11.27it/s]
+Epoch 2018/4000: 100%|██████████| 10/10 [00:00<00:00, 15.04it/s]
+Epoch 2018/4000: 100%|██████████| 10/10 [00:01<00:00,  9.31it/s]
+epoch: 2017, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.353107, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2019/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2019/4000:  10%|█         | 1/10 [00:00<00:05,  1.51it/s]
+Epoch 2019/4000:  40%|████      | 4/10 [00:00<00:00,  6.20it/s]
+Epoch 2019/4000:  70%|███████   | 7/10 [00:00<00:00, 10.12it/s]
+Epoch 2019/4000: 100%|██████████| 10/10 [00:01<00:00, 13.59it/s]
+Epoch 2019/4000: 100%|██████████| 10/10 [00:01<00:00,  8.39it/s]
+epoch: 2018, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.349776, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2020/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2020/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 2020/4000:  30%|███       | 3/10 [00:00<00:01,  5.21it/s]
+Epoch 2020/4000:  60%|██████    | 6/10 [00:00<00:00,  9.87it/s]
+Epoch 2020/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.45it/s]
+Epoch 2020/4000: 100%|██████████| 10/10 [00:01<00:00,  8.78it/s]
+epoch: 2019, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.351198, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2021/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2021/4000:  10%|█         | 1/10 [00:00<00:05,  1.73it/s]
+Epoch 2021/4000:  40%|████      | 4/10 [00:00<00:00,  6.76it/s]
+Epoch 2021/4000:  70%|███████   | 7/10 [00:00<00:00, 11.29it/s]
+Epoch 2021/4000: 100%|██████████| 10/10 [00:00<00:00, 14.23it/s]
+Epoch 2021/4000: 100%|██████████| 10/10 [00:01<00:00,  9.07it/s]
+epoch: 2020, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.354303, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2022/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2022/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 2022/4000:  30%|███       | 3/10 [00:00<00:01,  5.26it/s]
+Epoch 2022/4000:  60%|██████    | 6/10 [00:00<00:00,  9.94it/s]
+Epoch 2022/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.72it/s]
+Epoch 2022/4000: 100%|██████████| 10/10 [00:01<00:00,  8.93it/s]
+epoch: 2021, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.351564, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2023/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2023/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 2023/4000:  40%|████      | 4/10 [00:00<00:00,  6.62it/s]
+Epoch 2023/4000:  70%|███████   | 7/10 [00:00<00:00, 10.46it/s]
+Epoch 2023/4000:  90%|█████████ | 9/10 [00:00<00:00, 12.41it/s]
+Epoch 2023/4000: 100%|██████████| 10/10 [00:01<00:00,  8.56it/s]
+epoch: 2022, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.349789, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2024/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2024/4000:  10%|█         | 1/10 [00:00<00:05,  1.56it/s]
+Epoch 2024/4000:  40%|████      | 4/10 [00:00<00:00,  6.38it/s]
+Epoch 2024/4000:  70%|███████   | 7/10 [00:00<00:00, 10.92it/s]
+Epoch 2024/4000: 100%|██████████| 10/10 [00:01<00:00, 14.31it/s]
+Epoch 2024/4000: 100%|██████████| 10/10 [00:01<00:00,  8.84it/s]
+epoch: 2023, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.349694, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2025/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2025/4000:  40%|████      | 4/10 [00:00<00:00,  6.88it/s]
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+Epoch 2026/4000: 100%|██████████| 10/10 [00:01<00:00, 13.84it/s]
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+Epoch 2027/4000: 100%|██████████| 10/10 [00:01<00:00, 14.00it/s]
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+Epoch 2038/4000: 100%|██████████| 10/10 [00:01<00:00,  9.07it/s]
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+Epoch 2127/4000: 100%|██████████| 10/10 [00:01<00:00,  8.65it/s]
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+Epoch 2203/4000: 100%|██████████| 10/10 [00:00<00:00, 14.17it/s]
+Epoch 2203/4000: 100%|██████████| 10/10 [00:01<00:00,  8.85it/s]
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+Epoch 2204/4000: 100%|██████████| 10/10 [00:00<00:00, 15.08it/s]
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+Learning rate updated: 4.606979898695191e-05
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+Epoch 2282/4000: 100%|██████████| 10/10 [00:01<00:00, 14.33it/s]
+Epoch 2282/4000: 100%|██████████| 10/10 [00:01<00:00,  8.55it/s]
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+Epoch 2283/4000: 100%|██████████| 10/10 [00:00<00:00, 14.62it/s]
+Epoch 2283/4000: 100%|██████████| 10/10 [00:01<00:00,  9.12it/s]
+Learning rate updated: 3.3865535638032174e-05
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+Epoch 2293/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.34it/s]
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+Epoch 2294/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.88it/s]
+Epoch 2294/4000: 100%|██████████| 10/10 [00:01<00:00,  9.00it/s]
+Learning rate updated: 3.2172258856130564e-05
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+Learning rate updated: 3.056364591332403e-05
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+Epoch 2306/4000: 100%|██████████| 10/10 [00:00<00:00, 14.38it/s]
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+Epoch 2307/4000: 100%|██████████| 10/10 [00:00<00:00, 14.96it/s]
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+Epoch 2308/4000: 100%|██████████| 10/10 [00:00<00:00, 14.80it/s]
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+Epoch 2359/4000:  70%|███████   | 7/10 [00:00<00:00,  9.90it/s]
+Epoch 2359/4000: 100%|██████████| 10/10 [00:01<00:00, 13.21it/s]
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+Epoch 2360/4000: 100%|██████████| 10/10 [00:01<00:00,  9.10it/s]
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+Epoch 2382/4000: 100%|██████████| 10/10 [00:01<00:00, 13.86it/s]
+Epoch 2382/4000: 100%|██████████| 10/10 [00:01<00:00,  8.47it/s]
+Learning rate updated: 2.134373384587749e-05
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+Epoch 2407/4000: 100%|██████████| 10/10 [00:00<00:00, 13.82it/s]
+Epoch 2407/4000: 100%|██████████| 10/10 [00:01<00:00,  8.77it/s]
+epoch: 2406, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.330655, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2408/4000:  10%|█         | 1/10 [00:00<00:05,  1.60it/s]
+Epoch 2408/4000:  30%|███       | 3/10 [00:00<00:01,  4.97it/s]
+Epoch 2408/4000:  50%|█████     | 5/10 [00:00<00:00,  7.99it/s]
+Epoch 2408/4000:  80%|████████  | 8/10 [00:00<00:00, 12.14it/s]
+Epoch 2408/4000: 100%|██████████| 10/10 [00:01<00:00,  8.42it/s]
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+Epoch 2409/4000:  70%|███████   | 7/10 [00:00<00:00, 10.40it/s]
+Epoch 2409/4000: 100%|██████████| 10/10 [00:01<00:00, 13.73it/s]
+Epoch 2409/4000: 100%|██████████| 10/10 [00:01<00:00,  8.55it/s]
+epoch: 2408, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.330186, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2410/4000:  30%|███       | 3/10 [00:00<00:01,  5.29it/s]
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+Epoch 2410/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.05it/s]
+Epoch 2410/4000: 100%|██████████| 10/10 [00:01<00:00,  9.11it/s]
+epoch: 2409, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.330239, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2411/4000:  70%|███████   | 7/10 [00:00<00:00, 11.24it/s]
+Epoch 2411/4000: 100%|██████████| 10/10 [00:00<00:00, 14.70it/s]
+Epoch 2411/4000: 100%|██████████| 10/10 [00:01<00:00,  9.09it/s]
+epoch: 2410, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.329596, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2412/4000: 100%|██████████| 10/10 [00:00<00:00, 14.92it/s]
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+Epoch 2413/4000: 100%|██████████| 10/10 [00:00<00:00, 14.97it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2414/4000:  70%|███████   | 7/10 [00:00<00:00, 11.20it/s]
+Epoch 2414/4000: 100%|██████████| 10/10 [00:00<00:00, 14.51it/s]
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+epoch: 2413, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.328852, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2415/4000:  70%|███████   | 7/10 [00:00<00:00, 11.41it/s]
+Epoch 2415/4000: 100%|██████████| 10/10 [00:00<00:00, 14.84it/s]
+Epoch 2415/4000: 100%|██████████| 10/10 [00:01<00:00,  9.16it/s]
+Learning rate updated: 1.829958380610921e-05
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2416/4000: 100%|██████████| 10/10 [00:00<00:00, 14.18it/s]
+Epoch 2416/4000: 100%|██████████| 10/10 [00:01<00:00,  8.74it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2417/4000: 100%|██████████| 10/10 [00:00<00:00, 14.56it/s]
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+Epoch 2418/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.52it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2419/4000: 100%|██████████| 10/10 [00:00<00:00, 15.02it/s]
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+Epoch 2420/4000: 100%|██████████| 10/10 [00:00<00:00, 14.99it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2421/4000: 100%|██████████| 10/10 [00:00<00:00, 14.90it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2422/4000:  90%|█████████ | 9/10 [00:00<00:00, 12.98it/s]
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+Epoch 2424/4000: 100%|██████████| 10/10 [00:00<00:00, 14.67it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2425/4000: 100%|██████████| 10/10 [00:01<00:00,  8.77it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2426/4000: 100%|██████████| 10/10 [00:01<00:00, 14.16it/s]
+Epoch 2426/4000: 100%|██████████| 10/10 [00:01<00:00,  8.67it/s]
+Learning rate updated: 1.738460461580375e-05
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2427/4000: 100%|██████████| 10/10 [00:01<00:00,  8.87it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2429/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.55it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2431/4000: 100%|██████████| 10/10 [00:01<00:00, 14.34it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
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+Epoch 2433/4000:  40%|████      | 4/10 [00:00<00:00,  6.43it/s]
+Epoch 2433/4000:  70%|███████   | 7/10 [00:00<00:00, 10.63it/s]
+Epoch 2433/4000: 100%|██████████| 10/10 [00:01<00:00, 14.03it/s]
+Epoch 2433/4000: 100%|██████████| 10/10 [00:01<00:00,  8.74it/s]
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+Epoch 2434/4000:  70%|███████   | 7/10 [00:00<00:00, 10.86it/s]
+Epoch 2434/4000: 100%|██████████| 10/10 [00:00<00:00, 14.13it/s]
+Epoch 2434/4000: 100%|██████████| 10/10 [00:01<00:00,  8.85it/s]
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+Epoch 2435/4000:  70%|███████   | 7/10 [00:00<00:00, 11.67it/s]
+Epoch 2435/4000: 100%|██████████| 10/10 [00:00<00:00, 15.63it/s]
+Epoch 2435/4000: 100%|██████████| 10/10 [00:01<00:00,  9.18it/s]
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+Epoch 2436/4000:  70%|███████   | 7/10 [00:00<00:00,  9.85it/s]
+Epoch 2436/4000: 100%|██████████| 10/10 [00:01<00:00, 13.10it/s]
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+Epoch 2437/4000:  70%|███████   | 7/10 [00:00<00:00, 11.15it/s]
+Epoch 2437/4000: 100%|██████████| 10/10 [00:00<00:00, 14.65it/s]
+Epoch 2437/4000: 100%|██████████| 10/10 [00:01<00:00,  9.08it/s]
+Learning rate updated: 1.6515374385013564e-05
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+Epoch 2438/4000: 100%|██████████| 10/10 [00:01<00:00, 14.03it/s]
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+Epoch 2444/4000:  80%|████████  | 8/10 [00:00<00:00, 13.05it/s]
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+Epoch 2446/4000: 100%|██████████| 10/10 [00:00<00:00, 15.01it/s]
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+Epoch 2447/4000: 100%|██████████| 10/10 [00:00<00:00, 15.09it/s]
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+Epoch 2448/4000: 100%|██████████| 10/10 [00:01<00:00, 13.41it/s]
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+Learning rate updated: 1.5689605665762886e-05
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2510/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2510/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 2510/4000:  40%|████      | 4/10 [00:00<00:00,  7.37it/s]
+Epoch 2510/4000:  70%|███████   | 7/10 [00:00<00:00, 12.31it/s]
+Epoch 2510/4000: 100%|██████████| 10/10 [00:00<00:00, 16.07it/s]
+Epoch 2510/4000: 100%|██████████| 10/10 [00:01<00:00,  9.82it/s]
+epoch: 2509, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.325239, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2511/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2511/4000:  10%|█         | 1/10 [00:00<00:05,  1.64it/s]
+Epoch 2511/4000:  40%|████      | 4/10 [00:00<00:00,  6.53it/s]
+Epoch 2511/4000:  70%|███████   | 7/10 [00:00<00:00, 10.88it/s]
+Epoch 2511/4000: 100%|██████████| 10/10 [00:00<00:00, 14.15it/s]
+Epoch 2511/4000: 100%|██████████| 10/10 [00:01<00:00,  8.66it/s]
+epoch: 2510, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.326153, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2512/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2512/4000:  10%|█         | 1/10 [00:00<00:05,  1.64it/s]
+Epoch 2512/4000:  40%|████      | 4/10 [00:00<00:00,  6.62it/s]
+Epoch 2512/4000:  70%|███████   | 7/10 [00:00<00:00, 11.21it/s]
+Epoch 2512/4000: 100%|██████████| 10/10 [00:00<00:00, 14.56it/s]
+Epoch 2512/4000: 100%|██████████| 10/10 [00:01<00:00,  9.06it/s]
+Learning rate updated: 1.2140317781059316e-05
+epoch: 2511, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.325952, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2513/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 2513/4000:  30%|███       | 3/10 [00:00<00:01,  5.66it/s]
+Epoch 2513/4000:  60%|██████    | 6/10 [00:00<00:00, 10.57it/s]
+Epoch 2513/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.49it/s]
+Epoch 2513/4000: 100%|██████████| 10/10 [00:01<00:00,  9.49it/s]
+epoch: 2512, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.325583, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2514/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2514/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 2514/4000:  40%|████      | 4/10 [00:00<00:00,  6.84it/s]
+Epoch 2514/4000:  80%|████████  | 8/10 [00:00<00:00, 12.74it/s]
+Epoch 2514/4000: 100%|██████████| 10/10 [00:01<00:00,  9.47it/s]
+epoch: 2513, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.325632, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2515/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2515/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 2515/4000:  40%|████      | 4/10 [00:00<00:00,  7.25it/s]
+Epoch 2515/4000:  80%|████████  | 8/10 [00:00<00:00, 13.43it/s]
+Epoch 2515/4000: 100%|██████████| 10/10 [00:01<00:00,  9.90it/s]
+epoch: 2514, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.325703, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2516/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2516/4000:  40%|████      | 4/10 [00:00<00:00,  6.26it/s]
+Epoch 2516/4000:  70%|███████   | 7/10 [00:00<00:00, 10.03it/s]
+Epoch 2516/4000: 100%|██████████| 10/10 [00:01<00:00, 13.02it/s]
+Epoch 2516/4000: 100%|██████████| 10/10 [00:01<00:00,  8.45it/s]
+epoch: 2515, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.325825, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2517/4000:  40%|████      | 4/10 [00:00<00:01,  5.99it/s]
+Epoch 2517/4000:  70%|███████   | 7/10 [00:00<00:00, 10.07it/s]
+Epoch 2517/4000: 100%|██████████| 10/10 [00:01<00:00, 13.23it/s]
+Epoch 2517/4000: 100%|██████████| 10/10 [00:01<00:00,  8.25it/s]
+epoch: 2516, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.325606, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2518/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 2518/4000:  30%|███       | 3/10 [00:00<00:01,  5.19it/s]
+Epoch 2518/4000:  60%|██████    | 6/10 [00:00<00:00,  9.70it/s]
+Epoch 2518/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.29it/s]
+Epoch 2518/4000: 100%|██████████| 10/10 [00:01<00:00,  8.75it/s]
+epoch: 2517, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.325295, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2519/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2519/4000:  40%|████      | 4/10 [00:00<00:00,  6.11it/s]
+Epoch 2519/4000:  70%|███████   | 7/10 [00:00<00:00, 10.41it/s]
+Epoch 2519/4000: 100%|██████████| 10/10 [00:01<00:00, 14.38it/s]
+Epoch 2519/4000: 100%|██████████| 10/10 [00:01<00:00,  8.64it/s]
+epoch: 2518, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.324849, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2520/4000:  70%|███████   | 7/10 [00:00<00:00, 11.02it/s]
+Epoch 2520/4000: 100%|██████████| 10/10 [00:00<00:00, 14.07it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2521/4000:  40%|████      | 4/10 [00:00<00:00,  6.98it/s]
+Epoch 2521/4000:  70%|███████   | 7/10 [00:00<00:00, 11.82it/s]
+Epoch 2521/4000: 100%|██████████| 10/10 [00:00<00:00, 15.72it/s]
+Epoch 2521/4000: 100%|██████████| 10/10 [00:01<00:00,  9.54it/s]
+epoch: 2520, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.324413, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2522/4000:  40%|████      | 4/10 [00:00<00:00,  6.43it/s]
+Epoch 2522/4000:  70%|███████   | 7/10 [00:00<00:00, 10.54it/s]
+Epoch 2522/4000: 100%|██████████| 10/10 [00:01<00:00, 13.94it/s]
+Epoch 2522/4000: 100%|██████████| 10/10 [00:01<00:00,  8.77it/s]
+epoch: 2521, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.324629, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2523/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2523/4000:  10%|█         | 1/10 [00:00<00:05,  1.63it/s]
+Epoch 2523/4000:  40%|████      | 4/10 [00:00<00:00,  6.56it/s]
+Epoch 2523/4000:  70%|███████   | 7/10 [00:00<00:00, 10.83it/s]
+Epoch 2523/4000: 100%|██████████| 10/10 [00:01<00:00, 13.90it/s]
+Epoch 2523/4000: 100%|██████████| 10/10 [00:01<00:00,  8.78it/s]
+Learning rate updated: 1.153330189200635e-05
+epoch: 2522, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.325282, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2524/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2524/4000:  10%|█         | 1/10 [00:00<00:05,  1.57it/s]
+Epoch 2524/4000:  40%|████      | 4/10 [00:00<00:00,  6.32it/s]
+Epoch 2524/4000:  80%|████████  | 8/10 [00:00<00:00, 12.07it/s]
+Epoch 2524/4000: 100%|██████████| 10/10 [00:01<00:00,  8.85it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2525/4000:  30%|███       | 3/10 [00:00<00:01,  5.20it/s]
+Epoch 2525/4000:  50%|█████     | 5/10 [00:00<00:00,  8.23it/s]
+Epoch 2525/4000:  80%|████████  | 8/10 [00:00<00:00, 12.33it/s]
+Epoch 2525/4000: 100%|██████████| 10/10 [00:01<00:00,  8.72it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2526/4000:  70%|███████   | 7/10 [00:00<00:00, 10.82it/s]
+Epoch 2526/4000: 100%|██████████| 10/10 [00:01<00:00, 14.32it/s]
+Epoch 2526/4000: 100%|██████████| 10/10 [00:01<00:00,  8.74it/s]
+epoch: 2525, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.323613, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2527/4000:  30%|███       | 3/10 [00:00<00:01,  5.28it/s]
+Epoch 2527/4000:  60%|██████    | 6/10 [00:00<00:00, 10.02it/s]
+Epoch 2527/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.34it/s]
+Epoch 2527/4000: 100%|██████████| 10/10 [00:01<00:00,  8.96it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2528/4000: 100%|██████████| 10/10 [00:00<00:00, 14.44it/s]
+Epoch 2528/4000: 100%|██████████| 10/10 [00:01<00:00,  9.05it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2529/4000:  80%|████████  | 8/10 [00:00<00:00, 12.90it/s]
+Epoch 2529/4000: 100%|██████████| 10/10 [00:01<00:00,  9.57it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2530/4000:  70%|███████   | 7/10 [00:00<00:00, 11.52it/s]
+Epoch 2530/4000: 100%|██████████| 10/10 [00:00<00:00, 14.96it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2531/4000: 100%|██████████| 10/10 [00:00<00:00, 14.05it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2532/4000: 100%|██████████| 10/10 [00:00<00:00, 15.01it/s]
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+Epoch 2533/4000: 100%|██████████| 10/10 [00:00<00:00, 14.44it/s]
+Epoch 2533/4000: 100%|██████████| 10/10 [00:01<00:00,  9.15it/s]
+epoch: 2532, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.324248, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2534/4000:  70%|███████   | 7/10 [00:00<00:00, 12.20it/s]
+Epoch 2534/4000: 100%|██████████| 10/10 [00:00<00:00, 15.89it/s]
+Epoch 2534/4000: 100%|██████████| 10/10 [00:01<00:00,  9.73it/s]
+epoch: 2533, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.324259, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2535/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2535/4000: 100%|██████████| 10/10 [00:00<00:00, 14.76it/s]
+Epoch 2535/4000: 100%|██████████| 10/10 [00:01<00:00,  9.16it/s]
+Learning rate updated: 1.0956636797406032e-05
+epoch: 2534, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.323968, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
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+Epoch 2536/4000:  10%|█         | 1/10 [00:00<00:05,  1.73it/s]
+Epoch 2536/4000:  30%|███       | 3/10 [00:00<00:01,  5.31it/s]
+Epoch 2536/4000:  60%|██████    | 6/10 [00:00<00:00, 10.31it/s]
+Epoch 2536/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.69it/s]
+Epoch 2536/4000: 100%|██████████| 10/10 [00:01<00:00,  9.18it/s]
+epoch: 2535, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.324044, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2537/4000:  30%|███       | 3/10 [00:00<00:01,  5.18it/s]
+Epoch 2537/4000:  60%|██████    | 6/10 [00:00<00:00,  9.75it/s]
+Epoch 2537/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.50it/s]
+Epoch 2537/4000: 100%|██████████| 10/10 [00:01<00:00,  8.88it/s]
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+Epoch 2538/4000:  40%|████      | 4/10 [00:00<00:00,  6.95it/s]
+Epoch 2538/4000:  70%|███████   | 7/10 [00:00<00:00, 10.95it/s]
+Epoch 2538/4000: 100%|██████████| 10/10 [00:00<00:00, 14.50it/s]
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+Epoch 2539/4000:  80%|████████  | 8/10 [00:00<00:00, 14.81it/s]
+Epoch 2539/4000: 100%|██████████| 10/10 [00:00<00:00, 10.94it/s]
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+Epoch 2540/4000:  70%|███████   | 7/10 [00:00<00:00, 11.32it/s]
+Epoch 2540/4000: 100%|██████████| 10/10 [00:00<00:00, 14.88it/s]
+Epoch 2540/4000: 100%|██████████| 10/10 [00:01<00:00,  9.28it/s]
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+Epoch 2541/4000:  70%|███████   | 7/10 [00:00<00:00, 11.84it/s]
+Epoch 2541/4000: 100%|██████████| 10/10 [00:00<00:00, 15.26it/s]
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+Epoch 2542/4000:  70%|███████   | 7/10 [00:00<00:00, 10.83it/s]
+Epoch 2542/4000: 100%|██████████| 10/10 [00:00<00:00, 14.04it/s]
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+Epoch 2543/4000: 100%|██████████| 10/10 [00:00<00:00, 14.43it/s]
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+Epoch 2544/4000: 100%|██████████| 10/10 [00:00<00:00, 16.17it/s]
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+Epoch 2545/4000:  70%|███████   | 7/10 [00:00<00:00, 11.00it/s]
+Epoch 2545/4000: 100%|██████████| 10/10 [00:00<00:00, 14.67it/s]
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+Epoch 2546/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.01it/s]
+Epoch 2546/4000: 100%|██████████| 10/10 [00:01<00:00,  9.06it/s]
+Learning rate updated: 1.0408804957535729e-05
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+Epoch 2547/4000: 100%|██████████| 10/10 [00:00<00:00, 15.06it/s]
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+Epoch 2549/4000: 100%|██████████| 10/10 [00:00<00:00, 15.40it/s]
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+Epoch 2551/4000: 100%|██████████| 10/10 [00:01<00:00, 13.95it/s]
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+Epoch 2561/4000: 100%|██████████| 10/10 [00:00<00:00, 15.03it/s]
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+Epoch 2562/4000: 100%|██████████| 10/10 [00:00<00:00, 14.21it/s]
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+Epoch 2563/4000: 100%|██████████| 10/10 [00:00<00:00, 15.37it/s]
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+Learning rate updated: 9.393946474175994e-06
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+Epoch 2589/4000: 100%|██████████| 10/10 [00:00<00:00, 16.12it/s]
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+Learning rate updated: 8.478036692943835e-06
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+Learning rate updated: 8.054134858296643e-06
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+Epoch 2612/4000: 100%|██████████| 10/10 [00:01<00:00,  9.36it/s]
+epoch: 2611, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322210, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2613/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2613/4000:  10%|█         | 1/10 [00:00<00:05,  1.66it/s]
+Epoch 2613/4000:  30%|███       | 3/10 [00:00<00:01,  5.15it/s]
+Epoch 2613/4000:  50%|█████     | 5/10 [00:00<00:00,  8.30it/s]
+Epoch 2613/4000:  80%|████████  | 8/10 [00:00<00:00, 12.24it/s]
+Epoch 2613/4000: 100%|██████████| 10/10 [00:01<00:00,  8.62it/s]
+epoch: 2612, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.321968, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2614/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2614/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 2614/4000:  40%|████      | 4/10 [00:00<00:00,  6.64it/s]
+Epoch 2614/4000:  70%|███████   | 7/10 [00:00<00:00, 11.24it/s]
+Epoch 2614/4000: 100%|██████████| 10/10 [00:00<00:00, 14.78it/s]
+Epoch 2614/4000: 100%|██████████| 10/10 [00:01<00:00,  9.23it/s]
+Learning rate updated: 7.65142811538181e-06
+epoch: 2613, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322239, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2615/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2615/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 2615/4000:  40%|████      | 4/10 [00:00<00:00,  6.88it/s]
+Epoch 2615/4000:  70%|███████   | 7/10 [00:00<00:00, 11.62it/s]
+Epoch 2615/4000: 100%|██████████| 10/10 [00:00<00:00, 15.07it/s]
+Epoch 2615/4000: 100%|██████████| 10/10 [00:01<00:00,  9.35it/s]
+epoch: 2614, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322899, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2616/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2616/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 2616/4000:  40%|████      | 4/10 [00:00<00:00,  6.76it/s]
+Epoch 2616/4000:  70%|███████   | 7/10 [00:00<00:00, 11.20it/s]
+Epoch 2616/4000: 100%|██████████| 10/10 [00:00<00:00, 14.92it/s]
+Epoch 2616/4000: 100%|██████████| 10/10 [00:01<00:00,  9.32it/s]
+epoch: 2615, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.323002, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2617/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2617/4000:  10%|█         | 1/10 [00:00<00:05,  1.65it/s]
+Epoch 2617/4000:  40%|████      | 4/10 [00:00<00:00,  6.54it/s]
+Epoch 2617/4000:  70%|███████   | 7/10 [00:00<00:00, 10.71it/s]
+Epoch 2617/4000: 100%|██████████| 10/10 [00:01<00:00, 13.98it/s]
+Epoch 2617/4000: 100%|██████████| 10/10 [00:01<00:00,  8.85it/s]
+epoch: 2616, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322496, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2618/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2618/4000:  10%|█         | 1/10 [00:00<00:04,  2.01it/s]
+Epoch 2618/4000:  40%|████      | 4/10 [00:00<00:00,  7.72it/s]
+Epoch 2618/4000:  70%|███████   | 7/10 [00:00<00:00, 12.54it/s]
+Epoch 2618/4000: 100%|██████████| 10/10 [00:00<00:00, 15.84it/s]
+Epoch 2618/4000: 100%|██████████| 10/10 [00:00<00:00, 10.04it/s]
+epoch: 2617, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322115, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2619/4000:  40%|████      | 4/10 [00:00<00:00,  6.69it/s]
+Epoch 2619/4000:  70%|███████   | 7/10 [00:00<00:00, 11.23it/s]
+Epoch 2619/4000: 100%|██████████| 10/10 [00:00<00:00, 14.57it/s]
+Epoch 2619/4000: 100%|██████████| 10/10 [00:01<00:00,  9.06it/s]
+epoch: 2618, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322150, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2620/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2620/4000:  10%|█         | 1/10 [00:00<00:05,  1.57it/s]
+Epoch 2620/4000:  40%|████      | 4/10 [00:00<00:00,  6.39it/s]
+Epoch 2620/4000:  70%|███████   | 7/10 [00:00<00:00, 10.69it/s]
+Epoch 2620/4000: 100%|██████████| 10/10 [00:01<00:00, 14.01it/s]
+Epoch 2620/4000: 100%|██████████| 10/10 [00:01<00:00,  8.59it/s]
+epoch: 2619, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322152, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2621/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2621/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 2621/4000:  40%|████      | 4/10 [00:00<00:00,  6.71it/s]
+Epoch 2621/4000:  70%|███████   | 7/10 [00:00<00:00, 11.24it/s]
+Epoch 2621/4000: 100%|██████████| 10/10 [00:00<00:00, 14.69it/s]
+Epoch 2621/4000: 100%|██████████| 10/10 [00:01<00:00,  8.77it/s]
+epoch: 2620, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322149, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2622/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2622/4000:  40%|████      | 4/10 [00:00<00:00,  6.60it/s]
+Epoch 2622/4000:  70%|███████   | 7/10 [00:00<00:00, 11.22it/s]
+Epoch 2622/4000: 100%|██████████| 10/10 [00:00<00:00, 14.45it/s]
+Epoch 2622/4000: 100%|██████████| 10/10 [00:01<00:00,  9.13it/s]
+epoch: 2621, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322123, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2623/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 2623/4000:  70%|███████   | 7/10 [00:00<00:00, 11.46it/s]
+Epoch 2623/4000: 100%|██████████| 10/10 [00:00<00:00, 14.96it/s]
+Epoch 2623/4000: 100%|██████████| 10/10 [00:01<00:00,  9.24it/s]
+epoch: 2622, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322300, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2624/4000:  40%|████      | 4/10 [00:00<00:00,  6.43it/s]
+Epoch 2624/4000:  70%|███████   | 7/10 [00:00<00:00, 10.60it/s]
+Epoch 2624/4000: 100%|██████████| 10/10 [00:01<00:00, 14.02it/s]
+Epoch 2624/4000: 100%|██████████| 10/10 [00:01<00:00,  8.72it/s]
+epoch: 2623, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322247, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2625/4000:  70%|███████   | 7/10 [00:00<00:00, 10.73it/s]
+Epoch 2625/4000: 100%|██████████| 10/10 [00:01<00:00, 13.97it/s]
+Epoch 2625/4000: 100%|██████████| 10/10 [00:01<00:00,  8.82it/s]
+Learning rate updated: 7.26885670961272e-06
+epoch: 2624, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322070, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2626/4000:  10%|█         | 1/10 [00:00<00:05,  1.65it/s]
+Epoch 2626/4000:  30%|███       | 3/10 [00:00<00:01,  5.06it/s]
+Epoch 2626/4000:  60%|██████    | 6/10 [00:00<00:00,  9.89it/s]
+Epoch 2626/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.13it/s]
+Epoch 2626/4000: 100%|██████████| 10/10 [00:01<00:00,  8.91it/s]
+epoch: 2625, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322008, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2627/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2627/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 2627/4000:  40%|████      | 4/10 [00:00<00:00,  6.79it/s]
+Epoch 2627/4000:  70%|███████   | 7/10 [00:00<00:00, 11.00it/s]
+Epoch 2627/4000: 100%|██████████| 10/10 [00:00<00:00, 14.66it/s]
+Epoch 2627/4000: 100%|██████████| 10/10 [00:01<00:00,  9.13it/s]
+epoch: 2626, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322486, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2628/4000:  70%|███████   | 7/10 [00:00<00:00, 11.11it/s]
+Epoch 2628/4000: 100%|██████████| 10/10 [00:00<00:00, 14.49it/s]
+Epoch 2628/4000: 100%|██████████| 10/10 [00:01<00:00,  8.99it/s]
+epoch: 2627, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.322955, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2629/4000:  80%|████████  | 8/10 [00:00<00:00, 12.58it/s]
+Epoch 2629/4000: 100%|██████████| 10/10 [00:01<00:00,  9.23it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2630/4000:  70%|███████   | 7/10 [00:00<00:00, 10.66it/s]
+Epoch 2630/4000: 100%|██████████| 10/10 [00:01<00:00, 14.09it/s]
+Epoch 2630/4000: 100%|██████████| 10/10 [00:01<00:00,  8.76it/s]
+epoch: 2629, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.323386, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2631/4000:  30%|███       | 3/10 [00:00<00:01,  5.12it/s]
+Epoch 2631/4000:  60%|██████    | 6/10 [00:00<00:00,  9.87it/s]
+Epoch 2631/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.47it/s]
+Epoch 2631/4000: 100%|██████████| 10/10 [00:01<00:00,  8.76it/s]
+epoch: 2630, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.323269, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2632/4000:  70%|███████   | 7/10 [00:00<00:00, 11.43it/s]
+Epoch 2632/4000: 100%|██████████| 10/10 [00:00<00:00, 15.36it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2633/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.95it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2634/4000: 100%|██████████| 10/10 [00:00<00:00, 15.49it/s]
+Epoch 2634/4000: 100%|██████████| 10/10 [00:01<00:00,  9.68it/s]
+epoch: 2633, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.321716, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2635/4000:  70%|███████   | 7/10 [00:00<00:00, 10.94it/s]
+Epoch 2635/4000: 100%|██████████| 10/10 [00:00<00:00, 14.27it/s]
+Epoch 2635/4000: 100%|██████████| 10/10 [00:01<00:00,  9.03it/s]
+epoch: 2634, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.321255, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2636/4000:  70%|███████   | 7/10 [00:00<00:00, 10.36it/s]
+Epoch 2636/4000: 100%|██████████| 10/10 [00:01<00:00, 13.14it/s]
+Epoch 2636/4000: 100%|██████████| 10/10 [00:01<00:00,  8.34it/s]
+Learning rate updated: 6.905413874132084e-06
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2637/4000: 100%|██████████| 10/10 [00:00<00:00, 15.42it/s]
+Epoch 2637/4000: 100%|██████████| 10/10 [00:01<00:00,  9.71it/s]
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+Epoch 2663/4000: 100%|██████████| 10/10 [00:01<00:00,  9.04it/s]
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+Epoch 2664/4000: 100%|██████████| 10/10 [00:00<00:00, 15.37it/s]
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+Epoch 2665/4000: 100%|██████████| 10/10 [00:01<00:00, 13.89it/s]
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+Epoch 2667/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.80it/s]
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+Epoch 2689/4000:  30%|███       | 3/10 [00:00<00:01,  5.30it/s]
+Epoch 2689/4000:  60%|██████    | 6/10 [00:00<00:00,  9.93it/s]
+Epoch 2689/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.53it/s]
+Epoch 2689/4000: 100%|██████████| 10/10 [00:01<00:00,  8.99it/s]
+epoch: 2688, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318156, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
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+Epoch 2690/4000:  30%|███       | 3/10 [00:00<00:01,  5.61it/s]
+Epoch 2690/4000:  60%|██████    | 6/10 [00:00<00:00, 10.34it/s]
+Epoch 2690/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.25it/s]
+Epoch 2690/4000: 100%|██████████| 10/10 [00:01<00:00,  9.29it/s]
+epoch: 2689, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318248, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2691/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2691/4000:  10%|█         | 1/10 [00:00<00:05,  1.66it/s]
+Epoch 2691/4000:  40%|████      | 4/10 [00:00<00:00,  6.43it/s]
+Epoch 2691/4000:  70%|███████   | 7/10 [00:00<00:00, 10.43it/s]
+Epoch 2691/4000: 100%|██████████| 10/10 [00:01<00:00, 13.74it/s]
+Epoch 2691/4000: 100%|██████████| 10/10 [00:01<00:00,  8.78it/s]
+Learning rate updated: 5.34327762135143e-06
+epoch: 2690, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318320, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2692/4000:  40%|████      | 4/10 [00:00<00:00,  6.38it/s]
+Epoch 2692/4000:  70%|███████   | 7/10 [00:00<00:00, 10.72it/s]
+Epoch 2692/4000: 100%|██████████| 10/10 [00:01<00:00, 13.86it/s]
+Epoch 2692/4000: 100%|██████████| 10/10 [00:01<00:00,  8.84it/s]
+epoch: 2691, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318294, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2693/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2693/4000:  40%|████      | 4/10 [00:00<00:00,  6.93it/s]
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+Epoch 2693/4000: 100%|██████████| 10/10 [00:00<00:00, 14.68it/s]
+Epoch 2693/4000: 100%|██████████| 10/10 [00:01<00:00,  9.11it/s]
+epoch: 2692, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318913, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2694/4000:  80%|████████  | 8/10 [00:00<00:00, 13.31it/s]
+Epoch 2694/4000: 100%|██████████| 10/10 [00:01<00:00,  9.81it/s]
+epoch: 2693, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.319565, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2695/4000: 100%|██████████| 10/10 [00:00<00:00, 15.50it/s]
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+epoch: 2694, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.319879, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2696/4000:  70%|███████   | 7/10 [00:00<00:00, 10.80it/s]
+Epoch 2696/4000: 100%|██████████| 10/10 [00:00<00:00, 14.02it/s]
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+epoch: 2695, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.319445, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2697/4000: 100%|██████████| 10/10 [00:00<00:00, 15.20it/s]
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+epoch: 2696, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318993, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2698/4000: 100%|██████████| 10/10 [00:00<00:00, 14.60it/s]
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+epoch: 2699, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.319197, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2701/4000: 100%|██████████| 10/10 [00:00<00:00, 14.40it/s]
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+epoch: 2700, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.319265, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2702/4000: 100%|██████████| 10/10 [00:00<00:00, 15.58it/s]
+Epoch 2702/4000: 100%|██████████| 10/10 [00:01<00:00,  9.66it/s]
+Learning rate updated: 5.076113740283858e-06
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+Epoch 2707/4000: 100%|██████████| 10/10 [00:00<00:00, 14.02it/s]
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+Epoch 2709/4000: 100%|██████████| 10/10 [00:00<00:00, 14.92it/s]
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+Epoch 2711/4000: 100%|██████████| 10/10 [00:00<00:00, 14.61it/s]
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+Epoch 2712/4000: 100%|██████████| 10/10 [00:00<00:00, 14.68it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2713/4000: 100%|██████████| 10/10 [00:00<00:00, 15.38it/s]
+Epoch 2713/4000: 100%|██████████| 10/10 [00:01<00:00,  9.56it/s]
+Learning rate updated: 4.8223080532696655e-06
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+Epoch 2714/4000: 100%|██████████| 10/10 [00:00<00:00, 14.16it/s]
+Epoch 2714/4000: 100%|██████████| 10/10 [00:01<00:00,  8.91it/s]
+epoch: 2713, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318817, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2715/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2715/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 2715/4000:  30%|███       | 3/10 [00:00<00:01,  5.56it/s]
+Epoch 2715/4000:  60%|██████    | 6/10 [00:00<00:00, 10.18it/s]
+Epoch 2715/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.11it/s]
+Epoch 2715/4000: 100%|██████████| 10/10 [00:01<00:00,  9.25it/s]
+epoch: 2714, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318775, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2716/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2716/4000:  10%|█         | 1/10 [00:00<00:05,  1.77it/s]
+Epoch 2716/4000:  40%|████      | 4/10 [00:00<00:00,  7.06it/s]
+Epoch 2716/4000:  70%|███████   | 7/10 [00:00<00:00, 11.38it/s]
+Epoch 2716/4000: 100%|██████████| 10/10 [00:00<00:00, 14.74it/s]
+Epoch 2716/4000: 100%|██████████| 10/10 [00:01<00:00,  9.44it/s]
+epoch: 2715, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318754, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2717/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2717/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
+Epoch 2717/4000:  40%|████      | 4/10 [00:00<00:00,  7.16it/s]
+Epoch 2717/4000:  80%|████████  | 8/10 [00:00<00:00, 13.15it/s]
+Epoch 2717/4000: 100%|██████████| 10/10 [00:01<00:00,  9.75it/s]
+epoch: 2716, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318432, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2718/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2718/4000:  10%|█         | 1/10 [00:00<00:05,  1.75it/s]
+Epoch 2718/4000:  40%|████      | 4/10 [00:00<00:00,  6.94it/s]
+Epoch 2718/4000:  70%|███████   | 7/10 [00:00<00:00, 11.05it/s]
+Epoch 2718/4000: 100%|██████████| 10/10 [00:00<00:00, 14.39it/s]
+Epoch 2718/4000: 100%|██████████| 10/10 [00:01<00:00,  9.19it/s]
+epoch: 2717, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318264, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2719/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2719/4000:  10%|█         | 1/10 [00:00<00:04,  1.94it/s]
+Epoch 2719/4000:  40%|████      | 4/10 [00:00<00:00,  7.42it/s]
+Epoch 2719/4000:  70%|███████   | 7/10 [00:00<00:00, 11.95it/s]
+Epoch 2719/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.54it/s]
+Epoch 2719/4000: 100%|██████████| 10/10 [00:01<00:00,  9.52it/s]
+epoch: 2718, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318269, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2720/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2720/4000:  10%|█         | 1/10 [00:00<00:04,  1.95it/s]
+Epoch 2720/4000:  30%|███       | 3/10 [00:00<00:01,  5.85it/s]
+Epoch 2720/4000:  50%|█████     | 5/10 [00:00<00:00,  8.97it/s]
+Epoch 2720/4000:  80%|████████  | 8/10 [00:00<00:00, 13.25it/s]
+Epoch 2720/4000: 100%|██████████| 10/10 [00:01<00:00,  9.48it/s]
+epoch: 2719, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318228, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2721/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2721/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 2721/4000:  30%|███       | 3/10 [00:00<00:01,  5.43it/s]
+Epoch 2721/4000:  50%|█████     | 5/10 [00:00<00:00,  8.59it/s]
+Epoch 2721/4000:  80%|████████  | 8/10 [00:00<00:00, 12.54it/s]
+Epoch 2721/4000: 100%|██████████| 10/10 [00:01<00:00, 14.27it/s]
+Epoch 2721/4000: 100%|██████████| 10/10 [00:01<00:00,  8.84it/s]
+epoch: 2720, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318531, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2722/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2722/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 2722/4000:  30%|███       | 3/10 [00:00<00:01,  5.59it/s]
+Epoch 2722/4000:  60%|██████    | 6/10 [00:00<00:00, 10.20it/s]
+Epoch 2722/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.08it/s]
+Epoch 2722/4000: 100%|██████████| 10/10 [00:01<00:00,  9.35it/s]
+epoch: 2721, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318827, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2723/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2723/4000:  10%|█         | 1/10 [00:00<00:05,  1.80it/s]
+Epoch 2723/4000:  30%|███       | 3/10 [00:00<00:01,  5.49it/s]
+Epoch 2723/4000:  50%|█████     | 5/10 [00:00<00:00,  8.74it/s]
+Epoch 2723/4000:  80%|████████  | 8/10 [00:00<00:00, 12.82it/s]
+Epoch 2723/4000: 100%|██████████| 10/10 [00:01<00:00,  8.79it/s]
+epoch: 2722, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318973, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2724/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2724/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 2724/4000:  40%|████      | 4/10 [00:00<00:00,  6.59it/s]
+Epoch 2724/4000:  70%|███████   | 7/10 [00:00<00:00, 10.93it/s]
+Epoch 2724/4000: 100%|██████████| 10/10 [00:00<00:00, 14.57it/s]
+Epoch 2724/4000: 100%|██████████| 10/10 [00:01<00:00,  9.07it/s]
+Learning rate updated: 4.581192650606182e-06
+epoch: 2723, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318758, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2725/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2725/4000:  10%|█         | 1/10 [00:00<00:04,  1.83it/s]
+Epoch 2725/4000:  40%|████      | 4/10 [00:00<00:00,  7.04it/s]
+Epoch 2725/4000:  70%|███████   | 7/10 [00:00<00:00, 11.62it/s]
+Epoch 2725/4000: 100%|██████████| 10/10 [00:00<00:00, 15.40it/s]
+Epoch 2725/4000: 100%|██████████| 10/10 [00:01<00:00,  9.62it/s]
+epoch: 2724, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318292, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2726/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2726/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 2726/4000:  40%|████      | 4/10 [00:00<00:00,  6.92it/s]
+Epoch 2726/4000:  70%|███████   | 7/10 [00:00<00:00, 11.36it/s]
+Epoch 2726/4000: 100%|██████████| 10/10 [00:00<00:00, 14.59it/s]
+Epoch 2726/4000: 100%|██████████| 10/10 [00:01<00:00,  9.38it/s]
+epoch: 2725, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318321, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2727/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2727/4000:  10%|█         | 1/10 [00:00<00:04,  1.89it/s]
+Epoch 2727/4000:  40%|████      | 4/10 [00:00<00:00,  7.30it/s]
+Epoch 2727/4000:  70%|███████   | 7/10 [00:00<00:00, 12.25it/s]
+Epoch 2727/4000: 100%|██████████| 10/10 [00:00<00:00, 15.99it/s]
+Epoch 2727/4000: 100%|██████████| 10/10 [00:01<00:00,  9.89it/s]
+epoch: 2726, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318701, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2728/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2728/4000:  10%|█         | 1/10 [00:00<00:05,  1.69it/s]
+Epoch 2728/4000:  40%|████      | 4/10 [00:00<00:00,  6.67it/s]
+Epoch 2728/4000:  70%|███████   | 7/10 [00:00<00:00, 11.06it/s]
+Epoch 2728/4000: 100%|██████████| 10/10 [00:00<00:00, 14.08it/s]
+Epoch 2728/4000: 100%|██████████| 10/10 [00:01<00:00,  8.88it/s]
+epoch: 2727, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318814, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2729/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2729/4000:  10%|█         | 1/10 [00:00<00:05,  1.79it/s]
+Epoch 2729/4000:  40%|████      | 4/10 [00:00<00:00,  7.01it/s]
+Epoch 2729/4000:  70%|███████   | 7/10 [00:00<00:00, 11.59it/s]
+Epoch 2729/4000: 100%|██████████| 10/10 [00:00<00:00, 14.83it/s]
+Epoch 2729/4000: 100%|██████████| 10/10 [00:01<00:00,  9.31it/s]
+epoch: 2728, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318713, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2730/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2730/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
+Epoch 2730/4000:  40%|████      | 4/10 [00:00<00:00,  6.98it/s]
+Epoch 2730/4000:  70%|███████   | 7/10 [00:00<00:00, 11.30it/s]
+Epoch 2730/4000: 100%|██████████| 10/10 [00:00<00:00, 14.76it/s]
+Epoch 2730/4000: 100%|██████████| 10/10 [00:01<00:00,  9.27it/s]
+epoch: 2729, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318408, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2731/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2731/4000:  10%|█         | 1/10 [00:00<00:05,  1.65it/s]
+Epoch 2731/4000:  40%|████      | 4/10 [00:00<00:00,  6.55it/s]
+Epoch 2731/4000:  70%|███████   | 7/10 [00:00<00:00, 10.91it/s]
+Epoch 2731/4000: 100%|██████████| 10/10 [00:00<00:00, 14.24it/s]
+Epoch 2731/4000: 100%|██████████| 10/10 [00:01<00:00,  8.93it/s]
+epoch: 2730, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.318180, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2732/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2732/4000:  10%|█         | 1/10 [00:00<00:05,  1.75it/s]
+Epoch 2732/4000:  40%|████      | 4/10 [00:00<00:00,  6.95it/s]
+Epoch 2732/4000:  70%|███████   | 7/10 [00:00<00:00, 11.47it/s]
+Epoch 2732/4000: 100%|██████████| 10/10 [00:00<00:00, 14.80it/s]
+Epoch 2732/4000: 100%|██████████| 10/10 [00:01<00:00,  9.16it/s]
+epoch: 2731, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.317992, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2733/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2733/4000:  10%|█         | 1/10 [00:00<00:06,  1.49it/s]
+Epoch 2733/4000:  30%|███       | 3/10 [00:00<00:01,  4.66it/s]
+Epoch 2733/4000:  60%|██████    | 6/10 [00:00<00:00,  9.11it/s]
+Epoch 2733/4000:  90%|█████████ | 9/10 [00:01<00:00, 12.81it/s]
+Epoch 2733/4000: 100%|██████████| 10/10 [00:01<00:00,  8.28it/s]
+epoch: 2732, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.317811, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2734/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2734/4000:  10%|█         | 1/10 [00:00<00:04,  1.90it/s]
+Epoch 2734/4000:  40%|████      | 4/10 [00:00<00:00,  7.38it/s]
+Epoch 2734/4000:  70%|███████   | 7/10 [00:00<00:00, 11.95it/s]
+Epoch 2734/4000: 100%|██████████| 10/10 [00:00<00:00, 15.57it/s]
+Epoch 2734/4000: 100%|██████████| 10/10 [00:01<00:00,  9.59it/s]
+epoch: 2733, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.317670, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2735/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2735/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 2735/4000:  40%|████      | 4/10 [00:00<00:00,  6.81it/s]
+Epoch 2735/4000:  70%|███████   | 7/10 [00:00<00:00, 11.53it/s]
+Epoch 2735/4000: 100%|██████████| 10/10 [00:00<00:00, 15.37it/s]
+Epoch 2735/4000: 100%|██████████| 10/10 [00:01<00:00,  9.37it/s]
+Learning rate updated: 4.3521330180758725e-06
+epoch: 2734, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.317429, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2736/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2736/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 2736/4000:  40%|████      | 4/10 [00:00<00:00,  6.64it/s]
+Epoch 2736/4000:  70%|███████   | 7/10 [00:00<00:00, 11.09it/s]
+Epoch 2736/4000: 100%|██████████| 10/10 [00:00<00:00, 14.66it/s]
+Epoch 2736/4000: 100%|██████████| 10/10 [00:01<00:00,  9.13it/s]
+epoch: 2735, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.317090, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2737/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2737/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 2737/4000:  40%|████      | 4/10 [00:00<00:00,  6.90it/s]
+Epoch 2737/4000:  70%|███████   | 7/10 [00:00<00:00, 11.56it/s]
+Epoch 2737/4000: 100%|██████████| 10/10 [00:00<00:00, 14.91it/s]
+Epoch 2737/4000: 100%|██████████| 10/10 [00:01<00:00,  9.18it/s]
+epoch: 2736, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.317160, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2738/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2738/4000:  40%|████      | 4/10 [00:00<00:00,  6.75it/s]
+Epoch 2738/4000:  70%|███████   | 7/10 [00:00<00:00, 11.14it/s]
+Epoch 2738/4000: 100%|██████████| 10/10 [00:00<00:00, 14.63it/s]
+Epoch 2738/4000: 100%|██████████| 10/10 [00:01<00:00,  9.33it/s]
+epoch: 2737, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316997, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2739/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2739/4000:  70%|███████   | 7/10 [00:00<00:00, 11.68it/s]
+Epoch 2739/4000: 100%|██████████| 10/10 [00:00<00:00, 14.81it/s]
+Epoch 2739/4000: 100%|██████████| 10/10 [00:01<00:00,  9.56it/s]
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+
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+Epoch 2740/4000: 100%|██████████| 10/10 [00:00<00:00, 15.48it/s]
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+Epoch 2741/4000: 100%|██████████| 10/10 [00:00<00:00, 14.50it/s]
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+Epoch 2743/4000:  30%|███       | 3/10 [00:00<00:01,  5.54it/s]
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+Epoch 2743/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.81it/s]
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+Epoch 2744/4000:  70%|███████   | 7/10 [00:00<00:00, 11.14it/s]
+Epoch 2744/4000: 100%|██████████| 10/10 [00:00<00:00, 14.46it/s]
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+Epoch 2745/4000: 100%|██████████| 10/10 [00:00<00:00, 14.60it/s]
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+Epoch 2754/4000: 100%|██████████| 10/10 [00:00<00:00, 14.53it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2756/4000: 100%|██████████| 10/10 [00:00<00:00, 16.06it/s]
+Epoch 2756/4000: 100%|██████████| 10/10 [00:00<00:00, 10.06it/s]
+Learning rate updated: 4.1345263671720786e-06
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2766/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 2766/4000:  40%|████      | 4/10 [00:00<00:00,  7.25it/s]
+Epoch 2766/4000:  70%|███████   | 7/10 [00:00<00:00, 11.89it/s]
+Epoch 2766/4000: 100%|██████████| 10/10 [00:00<00:00, 15.29it/s]
+Epoch 2766/4000: 100%|██████████| 10/10 [00:01<00:00,  9.62it/s]
+epoch: 2765, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316230, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2767/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2767/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 2767/4000:  40%|████      | 4/10 [00:00<00:00,  6.91it/s]
+Epoch 2767/4000:  70%|███████   | 7/10 [00:00<00:00, 11.71it/s]
+Epoch 2767/4000: 100%|██████████| 10/10 [00:00<00:00, 14.99it/s]
+Epoch 2767/4000: 100%|██████████| 10/10 [00:01<00:00,  9.45it/s]
+Learning rate updated: 3.927800048813474e-06
+epoch: 2766, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316230, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2768/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2768/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 2768/4000:  40%|████      | 4/10 [00:00<00:00,  6.73it/s]
+Epoch 2768/4000:  70%|███████   | 7/10 [00:00<00:00, 11.42it/s]
+Epoch 2768/4000: 100%|██████████| 10/10 [00:00<00:00, 15.09it/s]
+Epoch 2768/4000: 100%|██████████| 10/10 [00:01<00:00,  9.35it/s]
+epoch: 2767, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316097, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2769/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2769/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 2769/4000:  30%|███       | 3/10 [00:00<00:01,  5.51it/s]
+Epoch 2769/4000:  60%|██████    | 6/10 [00:00<00:00, 10.12it/s]
+Epoch 2769/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.94it/s]
+Epoch 2769/4000: 100%|██████████| 10/10 [00:01<00:00,  9.20it/s]
+epoch: 2768, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316451, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2770/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2770/4000:  10%|█         | 1/10 [00:00<00:04,  1.89it/s]
+Epoch 2770/4000:  40%|████      | 4/10 [00:00<00:00,  7.50it/s]
+Epoch 2770/4000:  70%|███████   | 7/10 [00:00<00:00, 12.21it/s]
+Epoch 2770/4000: 100%|██████████| 10/10 [00:00<00:00, 15.52it/s]
+Epoch 2770/4000: 100%|██████████| 10/10 [00:01<00:00,  9.89it/s]
+epoch: 2769, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316661, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2771/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2771/4000:  10%|█         | 1/10 [00:00<00:04,  1.87it/s]
+Epoch 2771/4000:  40%|████      | 4/10 [00:00<00:00,  7.28it/s]
+Epoch 2771/4000:  70%|███████   | 7/10 [00:00<00:00, 12.12it/s]
+Epoch 2771/4000: 100%|██████████| 10/10 [00:00<00:00, 16.03it/s]
+Epoch 2771/4000: 100%|██████████| 10/10 [00:01<00:00, 10.00it/s]
+epoch: 2770, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316388, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2772/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2772/4000:  10%|█         | 1/10 [00:00<00:05,  1.80it/s]
+Epoch 2772/4000:  30%|███       | 3/10 [00:00<00:01,  5.50it/s]
+Epoch 2772/4000:  60%|██████    | 6/10 [00:00<00:00, 10.47it/s]
+Epoch 2772/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.25it/s]
+Epoch 2772/4000: 100%|██████████| 10/10 [00:01<00:00,  9.42it/s]
+epoch: 2771, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315907, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2773/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2773/4000:  10%|█         | 1/10 [00:00<00:04,  1.90it/s]
+Epoch 2773/4000:  40%|████      | 4/10 [00:00<00:00,  7.36it/s]
+Epoch 2773/4000:  70%|███████   | 7/10 [00:00<00:00, 12.13it/s]
+Epoch 2773/4000: 100%|██████████| 10/10 [00:00<00:00, 15.96it/s]
+Epoch 2773/4000: 100%|██████████| 10/10 [00:01<00:00,  9.78it/s]
+epoch: 2772, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315843, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2774/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2774/4000:  10%|█         | 1/10 [00:00<00:04,  1.87it/s]
+Epoch 2774/4000:  40%|████      | 4/10 [00:00<00:00,  7.22it/s]
+Epoch 2774/4000:  70%|███████   | 7/10 [00:00<00:00, 11.66it/s]
+Epoch 2774/4000: 100%|██████████| 10/10 [00:00<00:00, 14.90it/s]
+Epoch 2774/4000: 100%|██████████| 10/10 [00:01<00:00,  9.60it/s]
+epoch: 2773, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316326, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2775/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2775/4000:  10%|█         | 1/10 [00:00<00:04,  2.02it/s]
+Epoch 2775/4000:  40%|████      | 4/10 [00:00<00:00,  7.92it/s]
+Epoch 2775/4000:  80%|████████  | 8/10 [00:00<00:00, 14.25it/s]
+Epoch 2775/4000: 100%|██████████| 10/10 [00:00<00:00, 10.62it/s]
+epoch: 2774, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316368, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2776/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2776/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
+Epoch 2776/4000:  40%|████      | 4/10 [00:00<00:00,  6.85it/s]
+Epoch 2776/4000:  70%|███████   | 7/10 [00:00<00:00, 11.04it/s]
+Epoch 2776/4000: 100%|██████████| 10/10 [00:00<00:00, 14.24it/s]
+Epoch 2776/4000: 100%|██████████| 10/10 [00:01<00:00,  9.09it/s]
+epoch: 2775, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316388, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2777/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2777/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 2777/4000:  40%|████      | 4/10 [00:00<00:00,  7.25it/s]
+Epoch 2777/4000:  70%|███████   | 7/10 [00:00<00:00, 11.85it/s]
+Epoch 2777/4000: 100%|██████████| 10/10 [00:00<00:00, 15.07it/s]
+Epoch 2777/4000: 100%|██████████| 10/10 [00:01<00:00,  9.66it/s]
+epoch: 2776, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316453, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2778/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2778/4000:  10%|█         | 1/10 [00:00<00:04,  1.94it/s]
+Epoch 2778/4000:  40%|████      | 4/10 [00:00<00:00,  7.32it/s]
+Epoch 2778/4000:  70%|███████   | 7/10 [00:00<00:00, 11.80it/s]
+Epoch 2778/4000: 100%|██████████| 10/10 [00:00<00:00, 15.49it/s]
+Epoch 2778/4000: 100%|██████████| 10/10 [00:01<00:00,  9.87it/s]
+Learning rate updated: 3.7314100463728006e-06
+epoch: 2777, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316512, Val MSE:0.000003, Val CE:0.000005, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2779/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2779/4000:  40%|████      | 4/10 [00:00<00:00,  7.35it/s]
+Epoch 2779/4000:  70%|███████   | 7/10 [00:00<00:00, 11.84it/s]
+Epoch 2779/4000: 100%|██████████| 10/10 [00:00<00:00, 15.33it/s]
+Epoch 2779/4000: 100%|██████████| 10/10 [00:01<00:00,  9.78it/s]
+epoch: 2778, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316280, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2780/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2780/4000:  10%|█         | 1/10 [00:00<00:04,  1.94it/s]
+Epoch 2780/4000:  40%|████      | 4/10 [00:00<00:00,  7.53it/s]
+Epoch 2780/4000:  70%|███████   | 7/10 [00:00<00:00, 11.90it/s]
+Epoch 2780/4000: 100%|██████████| 10/10 [00:00<00:00, 15.57it/s]
+Epoch 2780/4000: 100%|██████████| 10/10 [00:01<00:00,  9.50it/s]
+epoch: 2779, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315983, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2781/4000:  70%|███████   | 7/10 [00:00<00:00, 10.51it/s]
+Epoch 2781/4000: 100%|██████████| 10/10 [00:01<00:00, 13.69it/s]
+Epoch 2781/4000: 100%|██████████| 10/10 [00:01<00:00,  8.58it/s]
+epoch: 2780, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315659, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2782/4000:  70%|███████   | 7/10 [00:00<00:00, 12.06it/s]
+Epoch 2782/4000: 100%|██████████| 10/10 [00:00<00:00, 14.98it/s]
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+epoch: 2781, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315585, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2783/4000: 100%|██████████| 10/10 [00:00<00:00, 14.38it/s]
+Epoch 2783/4000: 100%|██████████| 10/10 [00:01<00:00,  9.02it/s]
+epoch: 2782, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315405, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2784/4000:  40%|████      | 4/10 [00:00<00:00,  7.30it/s]
+Epoch 2784/4000:  70%|███████   | 7/10 [00:00<00:00, 11.87it/s]
+Epoch 2784/4000: 100%|██████████| 10/10 [00:00<00:00, 15.46it/s]
+Epoch 2784/4000: 100%|██████████| 10/10 [00:01<00:00,  9.83it/s]
+epoch: 2783, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315294, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2785/4000:  10%|█         | 1/10 [00:00<00:04,  1.90it/s]
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+Epoch 2785/4000:  70%|███████   | 7/10 [00:00<00:00, 12.25it/s]
+Epoch 2785/4000: 100%|██████████| 10/10 [00:00<00:00, 16.22it/s]
+Epoch 2785/4000: 100%|██████████| 10/10 [00:00<00:00, 10.06it/s]
+epoch: 2784, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315314, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2786/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.28it/s]
+Epoch 2786/4000: 100%|██████████| 10/10 [00:01<00:00,  9.36it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2787/4000:  70%|███████   | 7/10 [00:00<00:00, 11.91it/s]
+Epoch 2787/4000: 100%|██████████| 10/10 [00:00<00:00, 16.02it/s]
+Epoch 2787/4000: 100%|██████████| 10/10 [00:01<00:00,  9.89it/s]
+epoch: 2786, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316138, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2788/4000:  70%|███████   | 7/10 [00:00<00:00, 11.43it/s]
+Epoch 2788/4000: 100%|██████████| 10/10 [00:00<00:00, 14.79it/s]
+Epoch 2788/4000: 100%|██████████| 10/10 [00:01<00:00,  9.50it/s]
+epoch: 2787, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316577, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2789/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2789/4000:  40%|████      | 4/10 [00:00<00:00,  7.25it/s]
+Epoch 2789/4000:  70%|███████   | 7/10 [00:00<00:00, 12.06it/s]
+Epoch 2789/4000: 100%|██████████| 10/10 [00:00<00:00, 15.75it/s]
+Epoch 2789/4000: 100%|██████████| 10/10 [00:01<00:00,  9.56it/s]
+Learning rate updated: 3.5448395440541604e-06
+epoch: 2788, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316325, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2790/4000: 100%|██████████| 10/10 [00:00<00:00, 15.24it/s]
+Epoch 2790/4000: 100%|██████████| 10/10 [00:01<00:00,  9.41it/s]
+epoch: 2789, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315986, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2791/4000: 100%|██████████| 10/10 [00:01<00:00,  9.48it/s]
+epoch: 2790, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315633, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2792/4000:  10%|█         | 1/10 [00:00<00:05,  1.77it/s]
+Epoch 2792/4000:  40%|████      | 4/10 [00:00<00:00,  7.08it/s]
+Epoch 2792/4000:  70%|███████   | 7/10 [00:00<00:00, 11.57it/s]
+Epoch 2792/4000: 100%|██████████| 10/10 [00:00<00:00, 14.84it/s]
+Epoch 2792/4000: 100%|██████████| 10/10 [00:01<00:00,  9.47it/s]
+epoch: 2791, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315571, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2793/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2793/4000:  30%|███       | 3/10 [00:00<00:01,  5.64it/s]
+Epoch 2793/4000:  60%|██████    | 6/10 [00:00<00:00, 10.61it/s]
+Epoch 2793/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.53it/s]
+Epoch 2793/4000: 100%|██████████| 10/10 [00:01<00:00,  9.54it/s]
+epoch: 2792, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315506, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2794/4000:  40%|████      | 4/10 [00:00<00:00,  7.32it/s]
+Epoch 2794/4000:  70%|███████   | 7/10 [00:00<00:00, 12.19it/s]
+Epoch 2794/4000: 100%|██████████| 10/10 [00:00<00:00, 15.58it/s]
+Epoch 2794/4000: 100%|██████████| 10/10 [00:01<00:00,  9.82it/s]
+epoch: 2793, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315541, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2795/4000:  40%|████      | 4/10 [00:00<00:00,  7.02it/s]
+Epoch 2795/4000:  70%|███████   | 7/10 [00:00<00:00, 11.30it/s]
+Epoch 2795/4000: 100%|██████████| 10/10 [00:00<00:00, 14.99it/s]
+Epoch 2795/4000: 100%|██████████| 10/10 [00:01<00:00,  9.32it/s]
+epoch: 2794, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315589, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2796/4000:  40%|████      | 4/10 [00:00<00:00,  6.92it/s]
+Epoch 2796/4000:  70%|███████   | 7/10 [00:00<00:00, 11.31it/s]
+Epoch 2796/4000: 100%|██████████| 10/10 [00:00<00:00, 14.80it/s]
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+epoch: 2795, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315753, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2797/4000:  70%|███████   | 7/10 [00:00<00:00, 12.18it/s]
+Epoch 2797/4000: 100%|██████████| 10/10 [00:00<00:00, 16.12it/s]
+Epoch 2797/4000: 100%|██████████| 10/10 [00:00<00:00, 10.08it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2798/4000:  70%|███████   | 7/10 [00:00<00:00, 11.61it/s]
+Epoch 2798/4000: 100%|██████████| 10/10 [00:00<00:00, 14.77it/s]
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+epoch: 2797, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316076, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2799/4000:  70%|███████   | 7/10 [00:00<00:00, 11.57it/s]
+Epoch 2799/4000: 100%|██████████| 10/10 [00:00<00:00, 15.24it/s]
+Epoch 2799/4000: 100%|██████████| 10/10 [00:01<00:00,  9.38it/s]
+epoch: 2798, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316273, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2800/4000: 100%|██████████| 10/10 [00:00<00:00, 14.88it/s]
+Epoch 2800/4000: 100%|██████████| 10/10 [00:01<00:00,  9.15it/s]
+Learning rate updated: 3.3675975668514524e-06
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+epoch: 2804, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.316135, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2807/4000: 100%|██████████| 10/10 [00:00<00:00, 15.28it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2810/4000: 100%|██████████| 10/10 [00:00<00:00, 15.88it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+epoch: 2816, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314806, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2818/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2818/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 2818/4000:  40%|████      | 4/10 [00:00<00:00,  7.25it/s]
+Epoch 2818/4000:  70%|███████   | 7/10 [00:00<00:00, 11.83it/s]
+Epoch 2818/4000: 100%|██████████| 10/10 [00:00<00:00, 15.76it/s]
+Epoch 2818/4000: 100%|██████████| 10/10 [00:01<00:00,  9.81it/s]
+epoch: 2817, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314415, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2819/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2819/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 2819/4000:  40%|████      | 4/10 [00:00<00:00,  7.13it/s]
+Epoch 2819/4000:  70%|███████   | 7/10 [00:00<00:00, 11.48it/s]
+Epoch 2819/4000: 100%|██████████| 10/10 [00:00<00:00, 14.87it/s]
+Epoch 2819/4000: 100%|██████████| 10/10 [00:01<00:00,  9.38it/s]
+Learning rate updated: 3.1992176885088796e-06
+epoch: 2818, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314403, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2820/4000:  10%|█         | 1/10 [00:00<00:05,  1.72it/s]
+Epoch 2820/4000:  40%|████      | 4/10 [00:00<00:00,  6.92it/s]
+Epoch 2820/4000:  80%|████████  | 8/10 [00:00<00:00, 13.04it/s]
+Epoch 2820/4000: 100%|██████████| 10/10 [00:01<00:00,  9.68it/s]
+epoch: 2819, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314478, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2821/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2821/4000:  10%|█         | 1/10 [00:00<00:04,  1.83it/s]
+Epoch 2821/4000:  40%|████      | 4/10 [00:00<00:00,  7.31it/s]
+Epoch 2821/4000:  70%|███████   | 7/10 [00:00<00:00, 12.29it/s]
+Epoch 2821/4000: 100%|██████████| 10/10 [00:00<00:00, 15.53it/s]
+Epoch 2821/4000: 100%|██████████| 10/10 [00:01<00:00,  9.79it/s]
+epoch: 2820, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314470, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2822/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2822/4000:  10%|█         | 1/10 [00:00<00:04,  1.95it/s]
+Epoch 2822/4000:  40%|████      | 4/10 [00:00<00:00,  7.64it/s]
+Epoch 2822/4000:  70%|███████   | 7/10 [00:00<00:00, 12.63it/s]
+Epoch 2822/4000: 100%|██████████| 10/10 [00:00<00:00, 16.33it/s]
+Epoch 2822/4000: 100%|██████████| 10/10 [00:00<00:00, 10.28it/s]
+epoch: 2821, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314313, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2823/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2823/4000:  30%|███       | 3/10 [00:00<00:01,  5.75it/s]
+Epoch 2823/4000:  60%|██████    | 6/10 [00:00<00:00, 10.94it/s]
+Epoch 2823/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.82it/s]
+Epoch 2823/4000: 100%|██████████| 10/10 [00:01<00:00,  9.56it/s]
+epoch: 2822, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314397, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2824/4000:  40%|████      | 4/10 [00:00<00:00,  7.29it/s]
+Epoch 2824/4000:  70%|███████   | 7/10 [00:00<00:00, 12.27it/s]
+Epoch 2824/4000: 100%|██████████| 10/10 [00:00<00:00, 15.99it/s]
+Epoch 2824/4000: 100%|██████████| 10/10 [00:01<00:00,  9.94it/s]
+epoch: 2823, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314433, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2825/4000:  40%|████      | 4/10 [00:00<00:00,  7.27it/s]
+Epoch 2825/4000:  70%|███████   | 7/10 [00:00<00:00, 12.19it/s]
+Epoch 2825/4000: 100%|██████████| 10/10 [00:00<00:00, 15.35it/s]
+Epoch 2825/4000: 100%|██████████| 10/10 [00:01<00:00,  9.78it/s]
+epoch: 2824, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314370, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2826/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2826/4000:  40%|████      | 4/10 [00:00<00:00,  6.66it/s]
+Epoch 2826/4000:  70%|███████   | 7/10 [00:00<00:00, 11.26it/s]
+Epoch 2826/4000: 100%|██████████| 10/10 [00:00<00:00, 15.14it/s]
+Epoch 2826/4000: 100%|██████████| 10/10 [00:01<00:00,  9.22it/s]
+epoch: 2825, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313978, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2827/4000:  70%|███████   | 7/10 [00:00<00:00, 11.32it/s]
+Epoch 2827/4000: 100%|██████████| 10/10 [00:00<00:00, 14.93it/s]
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+Epoch 2828/4000:  40%|████      | 4/10 [00:00<00:00,  7.54it/s]
+Epoch 2828/4000:  70%|███████   | 7/10 [00:00<00:00, 12.56it/s]
+Epoch 2828/4000: 100%|██████████| 10/10 [00:00<00:00, 16.38it/s]
+Epoch 2828/4000: 100%|██████████| 10/10 [00:00<00:00, 10.14it/s]
+epoch: 2827, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314383, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2829/4000:  40%|████      | 4/10 [00:00<00:00,  7.48it/s]
+Epoch 2829/4000:  70%|███████   | 7/10 [00:00<00:00, 12.23it/s]
+Epoch 2829/4000: 100%|██████████| 10/10 [00:00<00:00, 15.57it/s]
+Epoch 2829/4000: 100%|██████████| 10/10 [00:01<00:00,  9.90it/s]
+epoch: 2828, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314485, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2830/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2830/4000:  70%|███████   | 7/10 [00:00<00:00, 11.85it/s]
+Epoch 2830/4000: 100%|██████████| 10/10 [00:00<00:00, 15.25it/s]
+Epoch 2830/4000: 100%|██████████| 10/10 [00:01<00:00,  9.64it/s]
+Learning rate updated: 3.0392568040834356e-06
+epoch: 2829, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314358, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2831/4000:  30%|███       | 3/10 [00:00<00:01,  6.03it/s]
+Epoch 2831/4000:  60%|██████    | 6/10 [00:00<00:00, 11.40it/s]
+Epoch 2831/4000:  90%|█████████ | 9/10 [00:00<00:00, 15.54it/s]
+Epoch 2831/4000: 100%|██████████| 10/10 [00:00<00:00, 10.14it/s]
+epoch: 2830, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314413, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2832/4000:  70%|███████   | 7/10 [00:00<00:00, 12.04it/s]
+Epoch 2832/4000: 100%|██████████| 10/10 [00:00<00:00, 15.34it/s]
+Epoch 2832/4000: 100%|██████████| 10/10 [00:01<00:00,  9.83it/s]
+epoch: 2831, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314646, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2833/4000:  70%|███████   | 7/10 [00:00<00:00, 11.63it/s]
+Epoch 2833/4000: 100%|██████████| 10/10 [00:00<00:00, 14.98it/s]
+Epoch 2833/4000: 100%|██████████| 10/10 [00:01<00:00,  9.29it/s]
+epoch: 2832, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314912, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2834/4000: 100%|██████████| 10/10 [00:01<00:00, 13.56it/s]
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+Epoch 2835/4000:  70%|███████   | 7/10 [00:00<00:00, 12.38it/s]
+Epoch 2835/4000: 100%|██████████| 10/10 [00:00<00:00, 15.70it/s]
+Epoch 2835/4000: 100%|██████████| 10/10 [00:01<00:00,  9.85it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2836/4000:  30%|███       | 3/10 [00:00<00:01,  5.54it/s]
+Epoch 2836/4000:  50%|█████     | 5/10 [00:00<00:00,  8.81it/s]
+Epoch 2836/4000:  80%|████████  | 8/10 [00:00<00:00, 13.19it/s]
+Epoch 2836/4000: 100%|██████████| 10/10 [00:01<00:00,  9.30it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2837/4000: 100%|██████████| 10/10 [00:00<00:00, 15.56it/s]
+Epoch 2837/4000: 100%|██████████| 10/10 [00:01<00:00,  9.89it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2839/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.95it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2840/4000: 100%|██████████| 10/10 [00:00<00:00, 15.59it/s]
+Epoch 2840/4000: 100%|██████████| 10/10 [00:01<00:00,  9.71it/s]
+epoch: 2839, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315027, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2841/4000:  70%|███████   | 7/10 [00:00<00:00, 11.40it/s]
+Epoch 2841/4000: 100%|██████████| 10/10 [00:00<00:00, 14.65it/s]
+Epoch 2841/4000: 100%|██████████| 10/10 [00:01<00:00,  9.43it/s]
+Learning rate updated: 2.8872939638792635e-06
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2842/4000: 100%|██████████| 10/10 [00:00<00:00, 16.56it/s]
+Epoch 2842/4000: 100%|██████████| 10/10 [00:00<00:00, 10.52it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2843/4000:  40%|████      | 4/10 [00:00<00:00,  7.06it/s]
+Epoch 2843/4000:  70%|███████   | 7/10 [00:00<00:00, 11.17it/s]
+Epoch 2843/4000: 100%|██████████| 10/10 [00:00<00:00, 14.55it/s]
+Epoch 2843/4000: 100%|██████████| 10/10 [00:01<00:00,  9.18it/s]
+epoch: 2842, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314355, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2844/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.35it/s]
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+Epoch 2845/4000: 100%|██████████| 10/10 [00:00<00:00, 16.61it/s]
+Epoch 2845/4000: 100%|██████████| 10/10 [00:00<00:00, 10.37it/s]
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+Epoch 2846/4000:  30%|███       | 3/10 [00:00<00:01,  4.70it/s]
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+Epoch 2846/4000:  90%|█████████ | 9/10 [00:01<00:00, 12.59it/s]
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+Epoch 2847/4000:  70%|███████   | 7/10 [00:00<00:00, 11.28it/s]
+Epoch 2847/4000: 100%|██████████| 10/10 [00:00<00:00, 14.81it/s]
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+epoch: 2846, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314989, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2848/4000: 100%|██████████| 10/10 [00:00<00:00, 14.86it/s]
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+Epoch 2850/4000: 100%|██████████| 10/10 [00:00<00:00, 14.54it/s]
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+Epoch 2851/4000: 100%|██████████| 10/10 [00:01<00:00, 13.87it/s]
+Epoch 2851/4000: 100%|██████████| 10/10 [00:01<00:00,  8.87it/s]
+epoch: 2850, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314796, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2852/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.00it/s]
+Epoch 2852/4000: 100%|██████████| 10/10 [00:01<00:00,  9.40it/s]
+Learning rate updated: 2.7429292656853003e-06
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+Epoch 2853/4000: 100%|██████████| 10/10 [00:00<00:00, 14.98it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2855/4000: 100%|██████████| 10/10 [00:00<00:00, 15.62it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2857/4000: 100%|██████████| 10/10 [00:00<00:00, 15.88it/s]
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+epoch: 2856, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315215, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2858/4000: 100%|██████████| 10/10 [00:00<00:00, 15.16it/s]
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+epoch: 2857, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.315016, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2859/4000: 100%|██████████| 10/10 [00:00<00:00, 15.15it/s]
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+Epoch 2862/4000: 100%|██████████| 10/10 [00:00<00:00, 14.33it/s]
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+epoch: 2861, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.314559, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2863/4000: 100%|██████████| 10/10 [00:00<00:00, 15.56it/s]
+Epoch 2863/4000: 100%|██████████| 10/10 [00:01<00:00,  9.70it/s]
+Learning rate updated: 2.605782802401035e-06
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2864/4000: 100%|██████████| 10/10 [00:00<00:00, 15.81it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2874/4000: 100%|██████████| 10/10 [00:01<00:00,  9.58it/s]
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+epoch: 2893, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313322, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2895/4000:  40%|████      | 4/10 [00:00<00:00,  6.72it/s]
+Epoch 2895/4000:  70%|███████   | 7/10 [00:00<00:00, 11.29it/s]
+Epoch 2895/4000: 100%|██████████| 10/10 [00:00<00:00, 14.78it/s]
+Epoch 2895/4000: 100%|██████████| 10/10 [00:01<00:00,  9.28it/s]
+epoch: 2894, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313361, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2896/4000:  40%|████      | 4/10 [00:00<00:00,  7.47it/s]
+Epoch 2896/4000:  70%|███████   | 7/10 [00:00<00:00, 11.76it/s]
+Epoch 2896/4000: 100%|██████████| 10/10 [00:00<00:00, 15.05it/s]
+Epoch 2896/4000: 100%|██████████| 10/10 [00:01<00:00,  9.73it/s]
+Learning rate updated: 2.234133030208587e-06
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+Epoch 2897/4000:  40%|████      | 4/10 [00:00<00:00,  7.61it/s]
+Epoch 2897/4000:  70%|███████   | 7/10 [00:00<00:00, 12.66it/s]
+Epoch 2897/4000: 100%|██████████| 10/10 [00:00<00:00, 16.10it/s]
+Epoch 2897/4000: 100%|██████████| 10/10 [00:00<00:00, 10.20it/s]
+epoch: 2896, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313359, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2898/4000:  40%|████      | 4/10 [00:00<00:00,  7.16it/s]
+Epoch 2898/4000:  70%|███████   | 7/10 [00:00<00:00, 11.39it/s]
+Epoch 2898/4000: 100%|██████████| 10/10 [00:00<00:00, 14.88it/s]
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+epoch: 2897, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313268, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2899/4000:  70%|███████   | 7/10 [00:00<00:00, 12.79it/s]
+Epoch 2899/4000: 100%|██████████| 10/10 [00:00<00:00, 16.55it/s]
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+epoch: 2898, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313254, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2901/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.65it/s]
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+Epoch 2902/4000:  90%|█████████ | 9/10 [00:01<00:00, 13.17it/s]
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+Epoch 2903/4000:  70%|███████   | 7/10 [00:00<00:00, 10.90it/s]
+Epoch 2903/4000: 100%|██████████| 10/10 [00:00<00:00, 14.74it/s]
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+Epoch 2904/4000: 100%|██████████| 10/10 [00:00<00:00, 15.42it/s]
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+Epoch 2905/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.14it/s]
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+epoch: 2904, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312866, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2906/4000: 100%|██████████| 10/10 [00:00<00:00, 15.45it/s]
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+epoch: 2905, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312844, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2907/4000: 100%|██████████| 10/10 [00:00<00:00, 14.61it/s]
+Epoch 2907/4000: 100%|██████████| 10/10 [00:01<00:00,  9.15it/s]
+Learning rate updated: 2.1224263786981576e-06
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+Epoch 2908/4000: 100%|██████████| 10/10 [00:00<00:00, 15.46it/s]
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+epoch: 2907, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312980, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2909/4000:  80%|████████  | 8/10 [00:00<00:00, 13.12it/s]
+Epoch 2909/4000: 100%|██████████| 10/10 [00:01<00:00,  9.30it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2910/4000: 100%|██████████| 10/10 [00:00<00:00, 14.93it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2911/4000: 100%|██████████| 10/10 [00:00<00:00, 15.70it/s]
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+Epoch 2912/4000: 100%|██████████| 10/10 [00:00<00:00, 14.80it/s]
+Epoch 2912/4000: 100%|██████████| 10/10 [00:01<00:00,  8.89it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2913/4000:  70%|███████   | 7/10 [00:00<00:00, 11.30it/s]
+Epoch 2913/4000: 100%|██████████| 10/10 [00:00<00:00, 14.53it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2914/4000:  70%|███████   | 7/10 [00:00<00:00, 10.92it/s]
+Epoch 2914/4000: 100%|██████████| 10/10 [00:00<00:00, 14.67it/s]
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+Epoch 2917/4000:  30%|███       | 3/10 [00:00<00:01,  5.84it/s]
+Epoch 2917/4000:  60%|██████    | 6/10 [00:00<00:00, 10.86it/s]
+Epoch 2917/4000:  90%|█████████ | 9/10 [00:00<00:00, 15.24it/s]
+Epoch 2917/4000: 100%|██████████| 10/10 [00:01<00:00,  9.92it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2918/4000: 100%|██████████| 10/10 [00:00<00:00, 14.58it/s]
+Epoch 2918/4000: 100%|██████████| 10/10 [00:01<00:00,  9.16it/s]
+Learning rate updated: 2.0163050597632494e-06
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2920/4000:  30%|███       | 3/10 [00:00<00:01,  5.22it/s]
+Epoch 2920/4000:  60%|██████    | 6/10 [00:00<00:00,  9.86it/s]
+Epoch 2920/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.61it/s]
+Epoch 2920/4000: 100%|██████████| 10/10 [00:01<00:00,  8.76it/s]
+epoch: 2919, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313601, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2921/4000:  40%|████      | 4/10 [00:00<00:00,  6.81it/s]
+Epoch 2921/4000:  70%|███████   | 7/10 [00:00<00:00, 10.95it/s]
+Epoch 2921/4000: 100%|██████████| 10/10 [00:00<00:00, 14.21it/s]
+Epoch 2921/4000: 100%|██████████| 10/10 [00:01<00:00,  8.97it/s]
+epoch: 2920, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313654, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2922/4000:  40%|████      | 4/10 [00:00<00:00,  6.84it/s]
+Epoch 2922/4000:  70%|███████   | 7/10 [00:00<00:00, 11.20it/s]
+Epoch 2922/4000: 100%|██████████| 10/10 [00:00<00:00, 14.09it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2923/4000:  40%|████      | 4/10 [00:00<00:00,  6.71it/s]
+Epoch 2923/4000:  70%|███████   | 7/10 [00:00<00:00, 11.04it/s]
+Epoch 2923/4000: 100%|██████████| 10/10 [00:00<00:00, 14.28it/s]
+Epoch 2923/4000: 100%|██████████| 10/10 [00:01<00:00,  9.05it/s]
+epoch: 2922, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313527, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2924/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2924/4000:  40%|████      | 4/10 [00:00<00:00,  6.76it/s]
+Epoch 2924/4000:  80%|████████  | 8/10 [00:00<00:00, 12.73it/s]
+Epoch 2924/4000: 100%|██████████| 10/10 [00:01<00:00,  9.43it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2925/4000:  70%|███████   | 7/10 [00:00<00:00, 11.32it/s]
+Epoch 2925/4000: 100%|██████████| 10/10 [00:00<00:00, 14.92it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2926/4000:  70%|███████   | 7/10 [00:00<00:00, 11.28it/s]
+Epoch 2926/4000: 100%|██████████| 10/10 [00:00<00:00, 14.87it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2927/4000:  30%|███       | 3/10 [00:00<00:01,  5.25it/s]
+Epoch 2927/4000:  50%|█████     | 5/10 [00:00<00:00,  8.42it/s]
+Epoch 2927/4000:  80%|████████  | 8/10 [00:00<00:00, 12.07it/s]
+Epoch 2927/4000: 100%|██████████| 10/10 [00:01<00:00,  8.48it/s]
+epoch: 2926, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.313232, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2928/4000:  40%|████      | 4/10 [00:00<00:00,  7.53it/s]
+Epoch 2928/4000:  80%|████████  | 8/10 [00:00<00:00, 13.79it/s]
+Epoch 2928/4000: 100%|██████████| 10/10 [00:01<00:00,  9.86it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2929/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2929/4000:  40%|████      | 4/10 [00:00<00:00,  6.74it/s]
+Epoch 2929/4000:  70%|███████   | 7/10 [00:00<00:00, 11.18it/s]
+Epoch 2929/4000: 100%|██████████| 10/10 [00:00<00:00, 14.92it/s]
+Epoch 2929/4000: 100%|██████████| 10/10 [00:01<00:00,  9.33it/s]
+Learning rate updated: 1.915489806775087e-06
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2930/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.54it/s]
+Epoch 2930/4000: 100%|██████████| 10/10 [00:01<00:00,  8.98it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2931/4000:  70%|███████   | 7/10 [00:00<00:00, 11.57it/s]
+Epoch 2931/4000: 100%|██████████| 10/10 [00:00<00:00, 15.21it/s]
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+Epoch 2932/4000: 100%|██████████| 10/10 [00:00<00:00, 14.03it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2933/4000: 100%|██████████| 10/10 [00:00<00:00, 15.07it/s]
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+Epoch 2934/4000:  70%|███████   | 7/10 [00:00<00:00, 11.35it/s]
+Epoch 2934/4000: 100%|██████████| 10/10 [00:00<00:00, 14.69it/s]
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+epoch: 2933, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312620, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2935/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.99it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2936/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.97it/s]
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+Epoch 2938/4000: 100%|██████████| 10/10 [00:00<00:00, 15.50it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2939/4000: 100%|██████████| 10/10 [00:00<00:00, 13.68it/s]
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+epoch: 2938, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312253, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2940/4000:  80%|████████  | 8/10 [00:00<00:00, 12.36it/s]
+Epoch 2940/4000: 100%|██████████| 10/10 [00:01<00:00,  8.40it/s]
+Learning rate updated: 1.8197153164363325e-06
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2941/4000: 100%|██████████| 10/10 [00:00<00:00, 15.12it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2946/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2946/4000:  10%|█         | 1/10 [00:00<00:05,  1.61it/s]
+Epoch 2946/4000:  40%|████      | 4/10 [00:00<00:00,  6.42it/s]
+Epoch 2946/4000:  70%|███████   | 7/10 [00:00<00:00, 10.68it/s]
+Epoch 2946/4000: 100%|██████████| 10/10 [00:01<00:00, 14.08it/s]
+Epoch 2946/4000: 100%|██████████| 10/10 [00:01<00:00,  8.79it/s]
+epoch: 2945, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311831, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2947/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2947/4000:  10%|█         | 1/10 [00:00<00:05,  1.67it/s]
+Epoch 2947/4000:  40%|████      | 4/10 [00:00<00:00,  6.57it/s]
+Epoch 2947/4000:  70%|███████   | 7/10 [00:00<00:00, 11.00it/s]
+Epoch 2947/4000: 100%|██████████| 10/10 [00:00<00:00, 14.31it/s]
+Epoch 2947/4000: 100%|██████████| 10/10 [00:01<00:00,  9.07it/s]
+epoch: 2946, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311903, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2948/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2948/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 2948/4000:  40%|████      | 4/10 [00:00<00:00,  7.34it/s]
+Epoch 2948/4000:  70%|███████   | 7/10 [00:00<00:00, 12.16it/s]
+Epoch 2948/4000: 100%|██████████| 10/10 [00:00<00:00, 14.73it/s]
+Epoch 2948/4000: 100%|██████████| 10/10 [00:01<00:00,  9.40it/s]
+epoch: 2947, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311890, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2949/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2949/4000:  10%|█         | 1/10 [00:00<00:04,  1.83it/s]
+Epoch 2949/4000:  40%|████      | 4/10 [00:00<00:00,  7.38it/s]
+Epoch 2949/4000:  80%|████████  | 8/10 [00:00<00:00, 13.43it/s]
+Epoch 2949/4000: 100%|██████████| 10/10 [00:01<00:00,  9.89it/s]
+epoch: 2948, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312089, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2950/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2950/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
+Epoch 2950/4000:  40%|████      | 4/10 [00:00<00:00,  7.39it/s]
+Epoch 2950/4000:  80%|████████  | 8/10 [00:00<00:00, 13.30it/s]
+Epoch 2950/4000: 100%|██████████| 10/10 [00:01<00:00,  9.58it/s]
+epoch: 2949, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312203, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2951/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2951/4000:  10%|█         | 1/10 [00:00<00:05,  1.64it/s]
+Epoch 2951/4000:  40%|████      | 4/10 [00:00<00:00,  6.48it/s]
+Epoch 2951/4000:  70%|███████   | 7/10 [00:00<00:00, 10.78it/s]
+Epoch 2951/4000: 100%|██████████| 10/10 [00:00<00:00, 14.49it/s]
+Epoch 2951/4000: 100%|██████████| 10/10 [00:01<00:00,  9.06it/s]
+Learning rate updated: 1.7287295506145157e-06
+epoch: 2950, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312004, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2952/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2952/4000:  10%|█         | 1/10 [00:00<00:04,  1.85it/s]
+Epoch 2952/4000:  30%|███       | 3/10 [00:00<00:01,  5.58it/s]
+Epoch 2952/4000:  60%|██████    | 6/10 [00:00<00:00, 10.20it/s]
+Epoch 2952/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.30it/s]
+Epoch 2952/4000: 100%|██████████| 10/10 [00:01<00:00,  9.16it/s]
+epoch: 2951, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311830, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2953/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2953/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 2953/4000:  40%|████      | 4/10 [00:00<00:00,  6.95it/s]
+Epoch 2953/4000:  70%|███████   | 7/10 [00:00<00:00, 11.35it/s]
+Epoch 2953/4000: 100%|██████████| 10/10 [00:00<00:00, 14.54it/s]
+Epoch 2953/4000: 100%|██████████| 10/10 [00:01<00:00,  9.37it/s]
+epoch: 2952, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311807, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2954/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2954/4000:  10%|█         | 1/10 [00:00<00:05,  1.79it/s]
+Epoch 2954/4000:  40%|████      | 4/10 [00:00<00:00,  6.90it/s]
+Epoch 2954/4000:  70%|███████   | 7/10 [00:00<00:00, 11.14it/s]
+Epoch 2954/4000: 100%|██████████| 10/10 [00:00<00:00, 14.52it/s]
+Epoch 2954/4000: 100%|██████████| 10/10 [00:01<00:00,  9.00it/s]
+epoch: 2953, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311855, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2955/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2955/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 2955/4000:  40%|████      | 4/10 [00:00<00:00,  7.30it/s]
+Epoch 2955/4000:  70%|███████   | 7/10 [00:00<00:00, 12.22it/s]
+Epoch 2955/4000: 100%|██████████| 10/10 [00:00<00:00, 15.88it/s]
+Epoch 2955/4000: 100%|██████████| 10/10 [00:01<00:00,  9.90it/s]
+epoch: 2954, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312037, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2956/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2956/4000:  10%|█         | 1/10 [00:00<00:04,  1.82it/s]
+Epoch 2956/4000:  30%|███       | 3/10 [00:00<00:01,  5.56it/s]
+Epoch 2956/4000:  50%|█████     | 5/10 [00:00<00:00,  8.79it/s]
+Epoch 2956/4000:  80%|████████  | 8/10 [00:00<00:00, 12.91it/s]
+Epoch 2956/4000: 100%|██████████| 10/10 [00:01<00:00,  9.33it/s]
+epoch: 2955, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312112, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2957/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2957/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 2957/4000:  40%|████      | 4/10 [00:00<00:00,  7.48it/s]
+Epoch 2957/4000:  80%|████████  | 8/10 [00:00<00:00, 13.85it/s]
+Epoch 2957/4000: 100%|██████████| 10/10 [00:00<00:00, 10.30it/s]
+epoch: 2956, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312138, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2958/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2958/4000:  10%|█         | 1/10 [00:00<00:05,  1.76it/s]
+Epoch 2958/4000:  30%|███       | 3/10 [00:00<00:01,  5.41it/s]
+Epoch 2958/4000:  60%|██████    | 6/10 [00:00<00:00,  9.96it/s]
+Epoch 2958/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.70it/s]
+Epoch 2958/4000: 100%|██████████| 10/10 [00:01<00:00,  9.17it/s]
+epoch: 2957, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312181, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2959/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2959/4000:  40%|████      | 4/10 [00:00<00:00,  7.05it/s]
+Epoch 2959/4000:  70%|███████   | 7/10 [00:00<00:00, 11.08it/s]
+Epoch 2959/4000: 100%|██████████| 10/10 [00:00<00:00, 14.57it/s]
+Epoch 2959/4000: 100%|██████████| 10/10 [00:01<00:00,  9.22it/s]
+epoch: 2958, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.312198, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2960/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 2960/4000:  40%|████      | 4/10 [00:00<00:00,  7.03it/s]
+Epoch 2960/4000:  70%|███████   | 7/10 [00:00<00:00, 11.62it/s]
+Epoch 2960/4000: 100%|██████████| 10/10 [00:00<00:00, 14.71it/s]
+Epoch 2960/4000: 100%|██████████| 10/10 [00:01<00:00,  9.38it/s]
+epoch: 2959, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311868, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2961/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2961/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 2961/4000:  40%|████      | 4/10 [00:00<00:00,  7.21it/s]
+Epoch 2961/4000:  80%|████████  | 8/10 [00:00<00:00, 13.12it/s]
+Epoch 2961/4000: 100%|██████████| 10/10 [00:01<00:00,  9.66it/s]
+epoch: 2960, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311662, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2962/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2962/4000:  10%|█         | 1/10 [00:00<00:05,  1.54it/s]
+Epoch 2962/4000:  40%|████      | 4/10 [00:00<00:00,  6.23it/s]
+Epoch 2962/4000:  70%|███████   | 7/10 [00:00<00:00, 10.52it/s]
+Epoch 2962/4000: 100%|██████████| 10/10 [00:01<00:00, 13.87it/s]
+Epoch 2962/4000: 100%|██████████| 10/10 [00:01<00:00,  8.74it/s]
+Learning rate updated: 1.6422930730837899e-06
+epoch: 2961, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311679, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2963/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2963/4000:  10%|█         | 1/10 [00:00<00:04,  1.95it/s]
+Epoch 2963/4000:  40%|████      | 4/10 [00:00<00:00,  7.59it/s]
+Epoch 2963/4000:  70%|███████   | 7/10 [00:00<00:00, 12.38it/s]
+Epoch 2963/4000: 100%|██████████| 10/10 [00:00<00:00, 15.49it/s]
+Epoch 2963/4000: 100%|██████████| 10/10 [00:01<00:00,  9.98it/s]
+epoch: 2962, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311798, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2964/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2964/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
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+Epoch 2964/4000:  70%|███████   | 7/10 [00:00<00:00, 11.52it/s]
+Epoch 2964/4000: 100%|██████████| 10/10 [00:00<00:00, 14.74it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2965/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2965/4000:  40%|████      | 4/10 [00:00<00:00,  6.73it/s]
+Epoch 2965/4000:  70%|███████   | 7/10 [00:00<00:00, 11.35it/s]
+Epoch 2965/4000: 100%|██████████| 10/10 [00:00<00:00, 14.77it/s]
+Epoch 2965/4000: 100%|██████████| 10/10 [00:01<00:00,  9.23it/s]
+epoch: 2964, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311711, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2966/4000:  40%|████      | 4/10 [00:00<00:00,  7.44it/s]
+Epoch 2966/4000:  70%|███████   | 7/10 [00:00<00:00, 12.17it/s]
+Epoch 2966/4000: 100%|██████████| 10/10 [00:00<00:00, 15.36it/s]
+Epoch 2966/4000: 100%|██████████| 10/10 [00:01<00:00,  9.85it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2967/4000:  70%|███████   | 7/10 [00:00<00:00, 11.66it/s]
+Epoch 2967/4000: 100%|██████████| 10/10 [00:00<00:00, 15.06it/s]
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+epoch: 2966, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311378, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2968/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
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+Epoch 2968/4000:  80%|████████  | 8/10 [00:00<00:00, 13.70it/s]
+Epoch 2968/4000: 100%|██████████| 10/10 [00:00<00:00, 10.01it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2969/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2969/4000:  10%|█         | 1/10 [00:00<00:04,  1.86it/s]
+Epoch 2969/4000:  40%|████      | 4/10 [00:00<00:00,  7.33it/s]
+Epoch 2969/4000:  80%|████████  | 8/10 [00:00<00:00, 13.55it/s]
+Epoch 2969/4000: 100%|██████████| 10/10 [00:00<00:00, 10.13it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2971/4000: 100%|██████████| 10/10 [00:00<00:00, 15.00it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2972/4000:  40%|████      | 4/10 [00:00<00:00,  8.01it/s]
+Epoch 2972/4000:  70%|███████   | 7/10 [00:00<00:00, 13.20it/s]
+Epoch 2972/4000: 100%|██████████| 10/10 [00:00<00:00, 17.25it/s]
+Epoch 2972/4000: 100%|██████████| 10/10 [00:00<00:00, 10.74it/s]
+epoch: 2971, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311440, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2973/4000:  40%|████      | 4/10 [00:00<00:00,  7.12it/s]
+Epoch 2973/4000:  70%|███████   | 7/10 [00:00<00:00, 11.26it/s]
+Epoch 2973/4000: 100%|██████████| 10/10 [00:00<00:00, 14.87it/s]
+Epoch 2973/4000: 100%|██████████| 10/10 [00:01<00:00,  9.14it/s]
+Learning rate updated: 1.5601784194296004e-06
+epoch: 2972, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311384, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2974/4000:  40%|████      | 4/10 [00:00<00:00,  6.93it/s]
+Epoch 2974/4000:  70%|███████   | 7/10 [00:00<00:00, 11.68it/s]
+Epoch 2974/4000: 100%|██████████| 10/10 [00:00<00:00, 15.54it/s]
+Epoch 2974/4000: 100%|██████████| 10/10 [00:01<00:00,  9.57it/s]
+epoch: 2973, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311214, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2975/4000:  30%|███       | 3/10 [00:00<00:01,  6.12it/s]
+Epoch 2975/4000:  60%|██████    | 6/10 [00:00<00:00, 10.99it/s]
+Epoch 2975/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.57it/s]
+Epoch 2975/4000: 100%|██████████| 10/10 [00:01<00:00,  9.81it/s]
+epoch: 2974, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311152, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2976/4000: 100%|██████████| 10/10 [00:00<00:00, 15.26it/s]
+Epoch 2976/4000: 100%|██████████| 10/10 [00:01<00:00,  9.59it/s]
+epoch: 2975, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311112, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2977/4000:  70%|███████   | 7/10 [00:00<00:00, 11.99it/s]
+Epoch 2977/4000: 100%|██████████| 10/10 [00:00<00:00, 15.92it/s]
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+epoch: 2976, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311151, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2978/4000: 100%|██████████| 10/10 [00:00<00:00, 14.50it/s]
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+epoch: 2977, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311441, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2979/4000: 100%|██████████| 10/10 [00:00<00:00, 15.13it/s]
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+epoch: 2978, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311673, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 2980/4000:  70%|███████   | 7/10 [00:00<00:00, 11.87it/s]
+Epoch 2980/4000: 100%|██████████| 10/10 [00:00<00:00, 15.78it/s]
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+epoch: 2979, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311596, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2982/4000: 100%|██████████| 10/10 [00:00<00:00, 14.62it/s]
+Epoch 2982/4000: 100%|██████████| 10/10 [00:01<00:00,  9.00it/s]
+epoch: 2981, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311429, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2983/4000:  90%|█████████ | 9/10 [00:00<00:00, 15.32it/s]
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+epoch: 2982, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311386, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2984/4000:  80%|████████  | 8/10 [00:00<00:00, 13.45it/s]
+Epoch 2984/4000: 100%|██████████| 10/10 [00:00<00:00, 10.03it/s]
+Learning rate updated: 1.4821694984581202e-06
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+Epoch 2985/4000: 100%|██████████| 10/10 [00:00<00:00, 16.04it/s]
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+epoch: 2984, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311358, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 2986/4000: 100%|██████████| 10/10 [00:00<00:00, 15.10it/s]
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+epoch: 2985, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311367, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3024/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3024/4000:  10%|█         | 1/10 [00:00<00:04,  1.88it/s]
+Epoch 3024/4000:  40%|████      | 4/10 [00:00<00:00,  7.16it/s]
+Epoch 3024/4000:  70%|███████   | 7/10 [00:00<00:00, 11.55it/s]
+Epoch 3024/4000: 100%|██████████| 10/10 [00:00<00:00, 15.25it/s]
+Epoch 3024/4000: 100%|██████████| 10/10 [00:01<00:00,  9.68it/s]
+epoch: 3023, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310599, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3025/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3025/4000:  10%|█         | 1/10 [00:00<00:04,  1.98it/s]
+Epoch 3025/4000:  30%|███       | 3/10 [00:00<00:01,  5.90it/s]
+Epoch 3025/4000:  60%|██████    | 6/10 [00:00<00:00, 11.15it/s]
+Epoch 3025/4000:  90%|█████████ | 9/10 [00:00<00:00, 15.45it/s]
+Epoch 3025/4000: 100%|██████████| 10/10 [00:01<00:00,  9.82it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3026/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3026/4000:  10%|█         | 1/10 [00:00<00:05,  1.80it/s]
+Epoch 3026/4000:  40%|████      | 4/10 [00:00<00:00,  7.17it/s]
+Epoch 3026/4000:  70%|███████   | 7/10 [00:00<00:00, 11.98it/s]
+Epoch 3026/4000: 100%|██████████| 10/10 [00:00<00:00, 15.30it/s]
+Epoch 3026/4000: 100%|██████████| 10/10 [00:01<00:00,  9.71it/s]
+epoch: 3025, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310391, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3027/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3027/4000:  10%|█         | 1/10 [00:00<00:04,  2.03it/s]
+Epoch 3027/4000:  40%|████      | 4/10 [00:00<00:00,  7.83it/s]
+Epoch 3027/4000:  70%|███████   | 7/10 [00:00<00:00, 12.82it/s]
+Epoch 3027/4000: 100%|██████████| 10/10 [00:00<00:00, 15.56it/s]
+Epoch 3027/4000: 100%|██████████| 10/10 [00:00<00:00, 10.15it/s]
+epoch: 3026, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310348, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3028/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3028/4000:  10%|█         | 1/10 [00:00<00:04,  1.94it/s]
+Epoch 3028/4000:  40%|████      | 4/10 [00:00<00:00,  7.61it/s]
+Epoch 3028/4000:  70%|███████   | 7/10 [00:00<00:00, 12.26it/s]
+Epoch 3028/4000: 100%|██████████| 10/10 [00:00<00:00, 15.49it/s]
+Epoch 3028/4000: 100%|██████████| 10/10 [00:00<00:00, 10.01it/s]
+Learning rate updated: 1.2072363200535042e-06
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3029/4000:  40%|████      | 4/10 [00:00<00:00,  7.74it/s]
+Epoch 3029/4000:  70%|███████   | 7/10 [00:00<00:00, 12.58it/s]
+Epoch 3029/4000: 100%|██████████| 10/10 [00:00<00:00, 16.01it/s]
+Epoch 3029/4000: 100%|██████████| 10/10 [00:00<00:00, 10.18it/s]
+epoch: 3028, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310385, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3030/4000:  40%|████      | 4/10 [00:00<00:00,  7.13it/s]
+Epoch 3030/4000:  70%|███████   | 7/10 [00:00<00:00, 11.70it/s]
+Epoch 3030/4000: 100%|██████████| 10/10 [00:00<00:00, 14.87it/s]
+Epoch 3030/4000: 100%|██████████| 10/10 [00:01<00:00,  9.54it/s]
+epoch: 3029, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310362, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3031/4000:  80%|████████  | 8/10 [00:00<00:00, 13.56it/s]
+Epoch 3031/4000: 100%|██████████| 10/10 [00:00<00:00, 10.03it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3032/4000:  40%|████      | 4/10 [00:00<00:00,  7.46it/s]
+Epoch 3032/4000:  70%|███████   | 7/10 [00:00<00:00, 12.40it/s]
+Epoch 3032/4000: 100%|██████████| 10/10 [00:00<00:00, 15.92it/s]
+Epoch 3032/4000: 100%|██████████| 10/10 [00:00<00:00, 10.15it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3033/4000:  40%|████      | 4/10 [00:00<00:00,  7.04it/s]
+Epoch 3033/4000:  70%|███████   | 7/10 [00:00<00:00, 11.54it/s]
+Epoch 3033/4000: 100%|██████████| 10/10 [00:00<00:00, 15.01it/s]
+Epoch 3033/4000: 100%|██████████| 10/10 [00:01<00:00,  9.55it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3034/4000:  40%|████      | 4/10 [00:00<00:00,  7.85it/s]
+Epoch 3034/4000:  70%|███████   | 7/10 [00:00<00:00, 12.65it/s]
+Epoch 3034/4000: 100%|██████████| 10/10 [00:00<00:00, 16.59it/s]
+Epoch 3034/4000: 100%|██████████| 10/10 [00:00<00:00, 10.25it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3035/4000:  70%|███████   | 7/10 [00:00<00:00, 11.98it/s]
+Epoch 3035/4000: 100%|██████████| 10/10 [00:00<00:00, 15.18it/s]
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+Epoch 3037/4000:  30%|███       | 3/10 [00:00<00:01,  5.54it/s]
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+Epoch 3037/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.17it/s]
+Epoch 3037/4000: 100%|██████████| 10/10 [00:01<00:00,  9.46it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3038/4000:  40%|████      | 4/10 [00:00<00:00,  7.56it/s]
+Epoch 3038/4000:  70%|███████   | 7/10 [00:00<00:00, 12.20it/s]
+Epoch 3038/4000: 100%|██████████| 10/10 [00:00<00:00, 16.01it/s]
+Epoch 3038/4000: 100%|██████████| 10/10 [00:01<00:00,  9.72it/s]
+epoch: 3037, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310008, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3039/4000:  30%|███       | 3/10 [00:00<00:01,  5.50it/s]
+Epoch 3039/4000:  60%|██████    | 6/10 [00:00<00:00, 10.23it/s]
+Epoch 3039/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.04it/s]
+Epoch 3039/4000: 100%|██████████| 10/10 [00:01<00:00,  9.23it/s]
+Learning rate updated: 1.146874504050829e-06
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3040/4000:  70%|███████   | 7/10 [00:00<00:00, 10.96it/s]
+Epoch 3040/4000: 100%|██████████| 10/10 [00:00<00:00, 14.21it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3041/4000: 100%|██████████| 10/10 [00:00<00:00, 16.62it/s]
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+Epoch 3042/4000: 100%|██████████| 10/10 [00:00<00:00, 14.13it/s]
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+Epoch 3043/4000:  70%|███████   | 7/10 [00:00<00:00, 11.52it/s]
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+Epoch 3044/4000: 100%|██████████| 10/10 [00:00<00:00, 15.18it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3045/4000: 100%|██████████| 10/10 [00:00<00:00, 15.77it/s]
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+Epoch 3049/4000: 100%|██████████| 10/10 [00:00<00:00, 14.61it/s]
+Epoch 3049/4000: 100%|██████████| 10/10 [00:01<00:00,  9.18it/s]
+epoch: 3048, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309672, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3050/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3050/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 3050/4000:  40%|████      | 4/10 [00:00<00:00,  7.30it/s]
+Epoch 3050/4000:  70%|███████   | 7/10 [00:00<00:00, 12.20it/s]
+Epoch 3050/4000: 100%|██████████| 10/10 [00:00<00:00, 16.26it/s]
+Epoch 3050/4000: 100%|██████████| 10/10 [00:01<00:00,  9.99it/s]
+Learning rate updated: 1.0895307788482876e-06
+epoch: 3049, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309637, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3051/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3051/4000:  10%|█         | 1/10 [00:00<00:04,  2.05it/s]
+Epoch 3051/4000:  40%|████      | 4/10 [00:00<00:00,  7.73it/s]
+Epoch 3051/4000:  70%|███████   | 7/10 [00:00<00:00, 12.44it/s]
+Epoch 3051/4000: 100%|██████████| 10/10 [00:00<00:00, 15.86it/s]
+Epoch 3051/4000: 100%|██████████| 10/10 [00:00<00:00, 10.22it/s]
+epoch: 3050, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309930, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3052/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3052/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
+Epoch 3052/4000:  40%|████      | 4/10 [00:00<00:00,  7.36it/s]
+Epoch 3052/4000:  70%|███████   | 7/10 [00:00<00:00, 12.12it/s]
+Epoch 3052/4000: 100%|██████████| 10/10 [00:00<00:00, 15.94it/s]
+Epoch 3052/4000: 100%|██████████| 10/10 [00:01<00:00,  9.94it/s]
+epoch: 3051, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310289, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3053/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3053/4000:  10%|█         | 1/10 [00:00<00:04,  2.02it/s]
+Epoch 3053/4000:  40%|████      | 4/10 [00:00<00:00,  7.92it/s]
+Epoch 3053/4000:  70%|███████   | 7/10 [00:00<00:00, 12.61it/s]
+Epoch 3053/4000: 100%|██████████| 10/10 [00:00<00:00, 15.64it/s]
+Epoch 3053/4000: 100%|██████████| 10/10 [00:00<00:00, 10.17it/s]
+epoch: 3052, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310480, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3054/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3054/4000:  10%|█         | 1/10 [00:00<00:04,  1.94it/s]
+Epoch 3054/4000:  40%|████      | 4/10 [00:00<00:00,  7.66it/s]
+Epoch 3054/4000:  70%|███████   | 7/10 [00:00<00:00, 12.55it/s]
+Epoch 3054/4000: 100%|██████████| 10/10 [00:00<00:00, 16.00it/s]
+Epoch 3054/4000: 100%|██████████| 10/10 [00:00<00:00, 10.15it/s]
+epoch: 3053, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310419, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3055/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3055/4000:  10%|█         | 1/10 [00:00<00:04,  2.08it/s]
+Epoch 3055/4000:  40%|████      | 4/10 [00:00<00:00,  7.89it/s]
+Epoch 3055/4000:  70%|███████   | 7/10 [00:00<00:00, 12.62it/s]
+Epoch 3055/4000: 100%|██████████| 10/10 [00:00<00:00, 15.58it/s]
+Epoch 3055/4000: 100%|██████████| 10/10 [00:00<00:00, 10.04it/s]
+epoch: 3054, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310339, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3056/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3056/4000:  10%|█         | 1/10 [00:00<00:05,  1.74it/s]
+Epoch 3056/4000:  40%|████      | 4/10 [00:00<00:00,  6.91it/s]
+Epoch 3056/4000:  70%|███████   | 7/10 [00:00<00:00, 11.65it/s]
+Epoch 3056/4000: 100%|██████████| 10/10 [00:00<00:00, 14.88it/s]
+Epoch 3056/4000: 100%|██████████| 10/10 [00:01<00:00,  9.43it/s]
+epoch: 3055, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310283, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3057/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3057/4000:  10%|█         | 1/10 [00:00<00:04,  2.06it/s]
+Epoch 3057/4000:  40%|████      | 4/10 [00:00<00:00,  7.98it/s]
+Epoch 3057/4000:  70%|███████   | 7/10 [00:00<00:00, 12.75it/s]
+Epoch 3057/4000: 100%|██████████| 10/10 [00:00<00:00, 15.61it/s]
+Epoch 3057/4000: 100%|██████████| 10/10 [00:01<00:00,  9.94it/s]
+epoch: 3056, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310301, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3058/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3058/4000:  10%|█         | 1/10 [00:00<00:05,  1.73it/s]
+Epoch 3058/4000:  40%|████      | 4/10 [00:00<00:00,  6.63it/s]
+Epoch 3058/4000:  70%|███████   | 7/10 [00:00<00:00, 10.87it/s]
+Epoch 3058/4000: 100%|██████████| 10/10 [00:00<00:00, 14.43it/s]
+Epoch 3058/4000: 100%|██████████| 10/10 [00:01<00:00,  9.17it/s]
+epoch: 3057, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310309, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3059/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3059/4000:  10%|█         | 1/10 [00:00<00:03,  2.32it/s]
+Epoch 3059/4000:  40%|████      | 4/10 [00:00<00:00,  8.31it/s]
+Epoch 3059/4000:  70%|███████   | 7/10 [00:00<00:00, 12.10it/s]
+Epoch 3059/4000: 100%|██████████| 10/10 [00:00<00:00, 15.49it/s]
+Epoch 3059/4000: 100%|██████████| 10/10 [00:00<00:00, 10.36it/s]
+epoch: 3058, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310282, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3060/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3060/4000:  10%|█         | 1/10 [00:00<00:04,  2.14it/s]
+Epoch 3060/4000:  40%|████      | 4/10 [00:00<00:00,  8.16it/s]
+Epoch 3060/4000:  70%|███████   | 7/10 [00:00<00:00, 13.04it/s]
+Epoch 3060/4000: 100%|██████████| 10/10 [00:00<00:00, 16.51it/s]
+Epoch 3060/4000: 100%|██████████| 10/10 [00:00<00:00, 10.59it/s]
+epoch: 3059, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310314, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3061/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3061/4000:  10%|█         | 1/10 [00:00<00:04,  1.92it/s]
+Epoch 3061/4000:  40%|████      | 4/10 [00:00<00:00,  7.37it/s]
+Epoch 3061/4000:  70%|███████   | 7/10 [00:00<00:00, 11.61it/s]
+Epoch 3061/4000: 100%|██████████| 10/10 [00:00<00:00, 15.37it/s]
+Epoch 3061/4000: 100%|██████████| 10/10 [00:01<00:00,  9.80it/s]
+Learning rate updated: 1.0350542399058731e-06
+epoch: 3060, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310375, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3062/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3062/4000:  10%|█         | 1/10 [00:00<00:04,  2.01it/s]
+Epoch 3062/4000:  40%|████      | 4/10 [00:00<00:00,  7.54it/s]
+Epoch 3062/4000:  70%|███████   | 7/10 [00:00<00:00, 11.96it/s]
+Epoch 3062/4000: 100%|██████████| 10/10 [00:00<00:00, 14.98it/s]
+Epoch 3062/4000: 100%|██████████| 10/10 [00:01<00:00,  9.18it/s]
+epoch: 3061, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310564, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3063/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3063/4000:  10%|█         | 1/10 [00:00<00:05,  1.70it/s]
+Epoch 3063/4000:  40%|████      | 4/10 [00:00<00:00,  6.77it/s]
+Epoch 3063/4000:  70%|███████   | 7/10 [00:00<00:00, 11.35it/s]
+Epoch 3063/4000: 100%|██████████| 10/10 [00:00<00:00, 15.09it/s]
+Epoch 3063/4000: 100%|██████████| 10/10 [00:01<00:00,  9.32it/s]
+epoch: 3062, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310655, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3064/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3064/4000:  10%|█         | 1/10 [00:00<00:04,  2.03it/s]
+Epoch 3064/4000:  40%|████      | 4/10 [00:01<00:01,  3.96it/s]
+Epoch 3064/4000:  70%|███████   | 7/10 [00:01<00:00,  7.41it/s]
+Epoch 3064/4000: 100%|██████████| 10/10 [00:01<00:00, 10.93it/s]
+Epoch 3064/4000: 100%|██████████| 10/10 [00:01<00:00,  7.12it/s]
+epoch: 3063, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310563, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3065/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3065/4000:  10%|█         | 1/10 [00:00<00:04,  1.95it/s]
+Epoch 3065/4000:  40%|████      | 4/10 [00:00<00:00,  7.72it/s]
+Epoch 3065/4000:  70%|███████   | 7/10 [00:00<00:00, 12.70it/s]
+Epoch 3065/4000: 100%|██████████| 10/10 [00:00<00:00, 16.64it/s]
+Epoch 3065/4000: 100%|██████████| 10/10 [00:00<00:00, 10.41it/s]
+epoch: 3064, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311043, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3066/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3066/4000:  10%|█         | 1/10 [00:00<00:04,  1.93it/s]
+Epoch 3066/4000:  40%|████      | 4/10 [00:00<00:00,  7.32it/s]
+Epoch 3066/4000:  70%|███████   | 7/10 [00:00<00:00, 12.06it/s]
+Epoch 3066/4000: 100%|██████████| 10/10 [00:00<00:00, 15.36it/s]
+Epoch 3066/4000: 100%|██████████| 10/10 [00:01<00:00,  9.88it/s]
+epoch: 3065, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311337, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3067/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3067/4000:  10%|█         | 1/10 [00:00<00:04,  1.99it/s]
+Epoch 3067/4000:  40%|████      | 4/10 [00:00<00:00,  7.76it/s]
+Epoch 3067/4000:  80%|████████  | 8/10 [00:00<00:00, 14.04it/s]
+Epoch 3067/4000: 100%|██████████| 10/10 [00:00<00:00, 10.35it/s]
+epoch: 3066, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311374, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3068/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3068/4000:  10%|█         | 1/10 [00:00<00:04,  1.88it/s]
+Epoch 3068/4000:  40%|████      | 4/10 [00:00<00:00,  7.59it/s]
+Epoch 3068/4000:  70%|███████   | 7/10 [00:00<00:00, 12.59it/s]
+Epoch 3068/4000: 100%|██████████| 10/10 [00:00<00:00, 16.42it/s]
+Epoch 3068/4000: 100%|██████████| 10/10 [00:00<00:00, 10.08it/s]
+epoch: 3067, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311246, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3069/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3069/4000:  10%|█         | 1/10 [00:00<00:04,  2.17it/s]
+Epoch 3069/4000:  40%|████      | 4/10 [00:00<00:00,  8.05it/s]
+Epoch 3069/4000:  70%|███████   | 7/10 [00:00<00:00, 13.03it/s]
+Epoch 3069/4000: 100%|██████████| 10/10 [00:00<00:00, 16.45it/s]
+Epoch 3069/4000: 100%|██████████| 10/10 [00:00<00:00, 10.40it/s]
+epoch: 3068, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310978, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3070/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3070/4000:  10%|█         | 1/10 [00:00<00:05,  1.66it/s]
+Epoch 3070/4000:  40%|████      | 4/10 [00:00<00:00,  6.80it/s]
+Epoch 3070/4000:  70%|███████   | 7/10 [00:00<00:00, 10.95it/s]
+Epoch 3070/4000: 100%|██████████| 10/10 [00:00<00:00, 14.56it/s]
+Epoch 3070/4000: 100%|██████████| 10/10 [00:01<00:00,  9.17it/s]
+epoch: 3069, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310775, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3071/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3071/4000:  10%|█         | 1/10 [00:00<00:04,  1.91it/s]
+Epoch 3071/4000:  40%|████      | 4/10 [00:00<00:00,  7.48it/s]
+Epoch 3071/4000:  80%|████████  | 8/10 [00:00<00:00, 13.61it/s]
+Epoch 3071/4000: 100%|██████████| 10/10 [00:00<00:00, 10.18it/s]
+epoch: 3070, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310590, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3072/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3072/4000:  10%|█         | 1/10 [00:00<00:04,  2.12it/s]
+Epoch 3072/4000:  40%|████      | 4/10 [00:00<00:00,  8.03it/s]
+Epoch 3072/4000:  70%|███████   | 7/10 [00:00<00:00, 13.13it/s]
+Epoch 3072/4000: 100%|██████████| 10/10 [00:00<00:00, 16.53it/s]
+Epoch 3072/4000: 100%|██████████| 10/10 [00:00<00:00, 10.61it/s]
+Learning rate updated: 9.833015279105794e-07
+epoch: 3071, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310319, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3073/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3073/4000:  10%|█         | 1/10 [00:00<00:04,  1.91it/s]
+Epoch 3073/4000:  40%|████      | 4/10 [00:00<00:00,  7.56it/s]
+Epoch 3073/4000:  80%|████████  | 8/10 [00:00<00:00, 13.83it/s]
+Epoch 3073/4000: 100%|██████████| 10/10 [00:00<00:00, 10.30it/s]
+epoch: 3072, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310126, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3074/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3074/4000:  10%|█         | 1/10 [00:00<00:04,  2.08it/s]
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+Epoch 3074/4000:  70%|███████   | 7/10 [00:00<00:00, 12.49it/s]
+Epoch 3074/4000: 100%|██████████| 10/10 [00:00<00:00, 16.09it/s]
+Epoch 3074/4000: 100%|██████████| 10/10 [00:00<00:00, 10.29it/s]
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+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3075/4000:  70%|███████   | 7/10 [00:00<00:00, 13.10it/s]
+Epoch 3075/4000: 100%|██████████| 10/10 [00:00<00:00, 16.43it/s]
+Epoch 3075/4000: 100%|██████████| 10/10 [00:00<00:00, 10.58it/s]
+epoch: 3074, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310062, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3076/4000:  70%|███████   | 7/10 [00:00<00:00, 12.38it/s]
+Epoch 3076/4000: 100%|██████████| 10/10 [00:00<00:00, 15.78it/s]
+Epoch 3076/4000: 100%|██████████| 10/10 [00:01<00:00,  9.89it/s]
+epoch: 3075, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309941, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3077/4000:  40%|████      | 4/10 [00:00<00:00,  7.02it/s]
+Epoch 3077/4000:  70%|███████   | 7/10 [00:00<00:00, 11.86it/s]
+Epoch 3077/4000: 100%|██████████| 10/10 [00:00<00:00, 15.32it/s]
+Epoch 3077/4000: 100%|██████████| 10/10 [00:01<00:00,  9.64it/s]
+epoch: 3076, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309951, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3078/4000:  40%|████      | 4/10 [00:00<00:00,  7.75it/s]
+Epoch 3078/4000:  70%|███████   | 7/10 [00:00<00:00, 11.96it/s]
+Epoch 3078/4000: 100%|██████████| 10/10 [00:00<00:00, 15.19it/s]
+Epoch 3078/4000: 100%|██████████| 10/10 [00:01<00:00,  9.85it/s]
+epoch: 3077, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310234, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3079/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3079/4000:  10%|█         | 1/10 [00:00<00:05,  1.71it/s]
+Epoch 3079/4000:  40%|████      | 4/10 [00:00<00:00,  6.80it/s]
+Epoch 3079/4000:  70%|███████   | 7/10 [00:00<00:00, 11.05it/s]
+Epoch 3079/4000: 100%|██████████| 10/10 [00:00<00:00, 14.37it/s]
+Epoch 3079/4000: 100%|██████████| 10/10 [00:01<00:00,  9.17it/s]
+epoch: 3078, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310401, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3080/4000:  70%|███████   | 7/10 [00:00<00:00, 11.66it/s]
+Epoch 3080/4000: 100%|██████████| 10/10 [00:00<00:00, 14.79it/s]
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+Epoch 3081/4000:  30%|███       | 3/10 [00:00<00:01,  5.22it/s]
+Epoch 3081/4000:  60%|██████    | 6/10 [00:00<00:00,  9.80it/s]
+Epoch 3081/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.44it/s]
+Epoch 3081/4000: 100%|██████████| 10/10 [00:01<00:00,  8.85it/s]
+epoch: 3080, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310291, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3082/4000:  40%|████      | 4/10 [00:00<00:00,  6.76it/s]
+Epoch 3082/4000:  70%|███████   | 7/10 [00:00<00:00, 11.26it/s]
+Epoch 3082/4000: 100%|██████████| 10/10 [00:00<00:00, 15.00it/s]
+Epoch 3082/4000: 100%|██████████| 10/10 [00:01<00:00,  9.39it/s]
+epoch: 3081, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310141, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3083/4000:  70%|███████   | 7/10 [00:00<00:00, 11.56it/s]
+Epoch 3083/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.47it/s]
+Epoch 3083/4000: 100%|██████████| 10/10 [00:01<00:00,  9.37it/s]
+Learning rate updated: 9.341364515150503e-07
+epoch: 3082, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310067, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3084/4000:  40%|████      | 4/10 [00:00<00:00,  6.37it/s]
+Epoch 3084/4000:  70%|███████   | 7/10 [00:00<00:00, 10.81it/s]
+Epoch 3084/4000: 100%|██████████| 10/10 [00:00<00:00, 14.46it/s]
+Epoch 3084/4000: 100%|██████████| 10/10 [00:01<00:00,  8.81it/s]
+epoch: 3083, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310199, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3085/4000:  30%|███       | 3/10 [00:00<00:01,  5.29it/s]
+Epoch 3085/4000:  60%|██████    | 6/10 [00:00<00:00, 10.32it/s]
+Epoch 3085/4000:  90%|█████████ | 9/10 [00:00<00:00, 14.59it/s]
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+epoch: 3084, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310240, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3086/4000:  70%|███████   | 7/10 [00:00<00:00, 13.15it/s]
+Epoch 3086/4000: 100%|██████████| 10/10 [00:00<00:00, 16.43it/s]
+Epoch 3086/4000: 100%|██████████| 10/10 [00:00<00:00, 10.63it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3087/4000:  70%|███████   | 7/10 [00:00<00:00, 10.89it/s]
+Epoch 3087/4000: 100%|██████████| 10/10 [00:00<00:00, 14.71it/s]
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+Epoch 3088/4000:  80%|████████  | 8/10 [00:00<00:00, 14.81it/s]
+Epoch 3088/4000: 100%|██████████| 10/10 [00:00<00:00, 11.06it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3089/4000:  40%|████      | 4/10 [00:01<00:01,  3.56it/s]
+Epoch 3089/4000:  70%|███████   | 7/10 [00:01<00:00,  6.66it/s]
+Epoch 3089/4000: 100%|██████████| 10/10 [00:01<00:00,  9.89it/s]
+Epoch 3089/4000: 100%|██████████| 10/10 [00:01<00:00,  6.38it/s]
+epoch: 3088, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309997, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3090/4000:  10%|█         | 1/10 [00:00<00:04,  1.93it/s]
+Epoch 3090/4000:  40%|████      | 4/10 [00:00<00:00,  7.37it/s]
+Epoch 3090/4000:  70%|███████   | 7/10 [00:00<00:00, 12.16it/s]
+Epoch 3090/4000: 100%|██████████| 10/10 [00:00<00:00, 15.43it/s]
+Epoch 3090/4000: 100%|██████████| 10/10 [00:01<00:00,  9.87it/s]
+epoch: 3089, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309950, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3091/4000:  70%|███████   | 7/10 [00:00<00:00, 11.72it/s]
+Epoch 3091/4000: 100%|██████████| 10/10 [00:00<00:00, 15.68it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3092/4000:  70%|███████   | 7/10 [00:00<00:00, 11.52it/s]
+Epoch 3092/4000: 100%|██████████| 10/10 [00:00<00:00, 14.87it/s]
+Epoch 3092/4000: 100%|██████████| 10/10 [00:01<00:00,  9.55it/s]
+epoch: 3091, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311085, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3093/4000:  40%|████      | 4/10 [00:00<00:00,  7.48it/s]
+Epoch 3093/4000:  70%|███████   | 7/10 [00:00<00:00, 12.20it/s]
+Epoch 3093/4000: 100%|██████████| 10/10 [00:00<00:00, 16.05it/s]
+Epoch 3093/4000: 100%|██████████| 10/10 [00:00<00:00, 10.09it/s]
+epoch: 3092, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.311261, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3094/4000:  70%|███████   | 7/10 [00:00<00:00, 11.54it/s]
+Epoch 3094/4000: 100%|██████████| 10/10 [00:00<00:00, 14.77it/s]
+Epoch 3094/4000: 100%|██████████| 10/10 [00:01<00:00,  9.42it/s]
+Learning rate updated: 8.874296289392978e-07
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3095/4000:  10%|█         | 1/10 [00:00<00:04,  1.84it/s]
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+Epoch 3095/4000:  70%|███████   | 7/10 [00:00<00:00, 12.09it/s]
+Epoch 3095/4000: 100%|██████████| 10/10 [00:00<00:00, 16.02it/s]
+Epoch 3095/4000: 100%|██████████| 10/10 [00:01<00:00,  9.96it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3096/4000:  70%|███████   | 7/10 [00:00<00:00, 11.18it/s]
+Epoch 3096/4000: 100%|██████████| 10/10 [00:00<00:00, 14.85it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3097/4000:  70%|███████   | 7/10 [00:00<00:00, 11.92it/s]
+Epoch 3097/4000: 100%|██████████| 10/10 [00:00<00:00, 15.55it/s]
+Epoch 3097/4000: 100%|██████████| 10/10 [00:01<00:00,  9.69it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3099/4000: 100%|██████████| 10/10 [00:00<00:00, 15.21it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3181/4000: 100%|██████████| 10/10 [00:00<00:00, 15.41it/s]
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+Epoch 3204/4000: 100%|██████████| 10/10 [00:00<00:00, 10.17it/s]
+Learning rate updated: 5.313368998205652e-07
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+Learning rate updated: 5.047700548295369e-07
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+Learning rate updated: 4.7953155208806e-07
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+Epoch 3231/4000: 100%|██████████| 10/10 [00:00<00:00, 14.60it/s]
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+Epoch 3232/4000: 100%|██████████| 10/10 [00:00<00:00, 15.24it/s]
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+Epoch 3307/4000: 100%|██████████| 10/10 [00:00<00:00, 15.15it/s]
+Epoch 3307/4000: 100%|██████████| 10/10 [00:01<00:00,  9.68it/s]
+epoch: 3306, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310410, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
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+Epoch 3308/4000:  10%|█         | 1/10 [00:00<00:05,  1.69it/s]
+Epoch 3308/4000:  40%|████      | 4/10 [00:00<00:00,  6.88it/s]
+Epoch 3308/4000:  70%|███████   | 7/10 [00:00<00:00, 11.51it/s]
+Epoch 3308/4000: 100%|██████████| 10/10 [00:00<00:00, 14.69it/s]
+Epoch 3308/4000: 100%|██████████| 10/10 [00:01<00:00,  9.28it/s]
+epoch: 3307, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310391, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3309/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3309/4000:  40%|████      | 4/10 [00:00<00:00,  8.17it/s]
+Epoch 3309/4000:  60%|██████    | 6/10 [00:01<00:00,  5.57it/s]
+Epoch 3309/4000:  90%|█████████ | 9/10 [00:01<00:00,  9.11it/s]
+Epoch 3309/4000: 100%|██████████| 10/10 [00:01<00:00,  7.26it/s]
+epoch: 3308, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310412, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3310/4000:  40%|████      | 4/10 [00:01<00:01,  4.06it/s]
+Epoch 3310/4000:  70%|███████   | 7/10 [00:01<00:00,  7.45it/s]
+Epoch 3310/4000: 100%|██████████| 10/10 [00:01<00:00, 10.94it/s]
+Epoch 3310/4000: 100%|██████████| 10/10 [00:01<00:00,  7.12it/s]
+Learning rate updated: 3.34874767476815e-07
+epoch: 3309, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310433, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3311/4000:  40%|████      | 4/10 [00:01<00:01,  3.82it/s]
+Epoch 3311/4000:  70%|███████   | 7/10 [00:01<00:00,  7.09it/s]
+Epoch 3311/4000: 100%|██████████| 10/10 [00:01<00:00, 10.28it/s]
+Epoch 3311/4000: 100%|██████████| 10/10 [00:01<00:00,  6.69it/s]
+epoch: 3310, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310417, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3312/4000:  30%|███       | 3/10 [00:00<00:01,  5.39it/s]
+Epoch 3312/4000:  50%|█████     | 5/10 [00:01<00:01,  4.29it/s]
+Epoch 3312/4000:  80%|████████  | 8/10 [00:01<00:00,  7.67it/s]
+Epoch 3312/4000: 100%|██████████| 10/10 [00:01<00:00,  6.43it/s]
+epoch: 3311, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310412, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3313/4000:  70%|███████   | 7/10 [00:01<00:00,  6.94it/s]
+Epoch 3313/4000: 100%|██████████| 10/10 [00:01<00:00, 10.10it/s]
+Epoch 3313/4000: 100%|██████████| 10/10 [00:01<00:00,  6.53it/s]
+epoch: 3312, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310435, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3314/4000:  60%|██████    | 6/10 [00:01<00:00,  5.56it/s]
+Epoch 3314/4000:  90%|█████████ | 9/10 [00:01<00:00,  8.90it/s]
+Epoch 3314/4000: 100%|██████████| 10/10 [00:01<00:00,  6.94it/s]
+epoch: 3313, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310436, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3315/4000:  70%|███████   | 7/10 [00:01<00:00,  6.91it/s]
+Epoch 3315/4000: 100%|██████████| 10/10 [00:01<00:00, 10.05it/s]
+Epoch 3315/4000: 100%|██████████| 10/10 [00:01<00:00,  6.68it/s]
+epoch: 3314, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310442, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3316/4000:  40%|████      | 4/10 [00:01<00:01,  4.09it/s]
+Epoch 3316/4000:  70%|███████   | 7/10 [00:01<00:00,  7.55it/s]
+Epoch 3316/4000: 100%|██████████| 10/10 [00:01<00:00, 10.90it/s]
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+epoch: 3315, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310445, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3317/4000:  50%|█████     | 5/10 [00:01<00:01,  4.63it/s]
+Epoch 3317/4000:  80%|████████  | 8/10 [00:01<00:00,  7.94it/s]
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+Epoch 3318/4000:  50%|█████     | 5/10 [00:01<00:01,  4.39it/s]
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+Epoch 3318/4000: 100%|██████████| 10/10 [00:01<00:00,  6.59it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3319/4000:  70%|███████   | 7/10 [00:01<00:00,  7.02it/s]
+Epoch 3319/4000: 100%|██████████| 10/10 [00:01<00:00, 10.11it/s]
+Epoch 3319/4000: 100%|██████████| 10/10 [00:01<00:00,  6.70it/s]
+epoch: 3318, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310394, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3320/4000:  70%|███████   | 7/10 [00:01<00:00,  7.09it/s]
+Epoch 3320/4000: 100%|██████████| 10/10 [00:01<00:00, 10.27it/s]
+Epoch 3320/4000: 100%|██████████| 10/10 [00:01<00:00,  6.73it/s]
+epoch: 3319, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310377, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3321/4000:  70%|███████   | 7/10 [00:00<00:00, 12.51it/s]
+Epoch 3321/4000: 100%|██████████| 10/10 [00:00<00:00, 15.90it/s]
+Epoch 3321/4000: 100%|██████████| 10/10 [00:01<00:00,  9.87it/s]
+Learning rate updated: 3.181310291029742e-07
+epoch: 3320, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310356, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3322/4000: 100%|██████████| 10/10 [00:01<00:00,  9.66it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3323/4000: 100%|██████████| 10/10 [00:00<00:00, 15.70it/s]
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+Epoch 3324/4000: 100%|██████████| 10/10 [00:00<00:00, 15.81it/s]
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+Epoch 3326/4000: 100%|██████████| 10/10 [00:00<00:00, 15.88it/s]
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+Epoch 3327/4000: 100%|██████████| 10/10 [00:00<00:00, 15.00it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+epoch: 3330, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.310230, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Learning rate updated: 3.0222447764782547e-07
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+Learning rate updated: 2.3385553964978208e-07
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3411/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3411/4000:  10%|█         | 1/10 [00:00<00:05,  1.68it/s]
+Epoch 3411/4000:  40%|████      | 4/10 [00:00<00:00,  6.53it/s]
+Epoch 3411/4000:  70%|███████   | 7/10 [00:00<00:00, 10.58it/s]
+Epoch 3411/4000: 100%|██████████| 10/10 [00:01<00:00, 13.89it/s]
+Epoch 3411/4000: 100%|██████████| 10/10 [00:01<00:00,  8.83it/s]
+epoch: 3410, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309583, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3412/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3412/4000:  10%|█         | 1/10 [00:00<00:03,  2.30it/s]
+Epoch 3412/4000:  40%|████      | 4/10 [00:00<00:00,  8.27it/s]
+Epoch 3412/4000:  70%|███████   | 7/10 [00:00<00:00, 13.34it/s]
+Epoch 3412/4000: 100%|██████████| 10/10 [00:00<00:00, 16.80it/s]
+Epoch 3412/4000: 100%|██████████| 10/10 [00:00<00:00, 10.50it/s]
+epoch: 3411, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309558, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3413/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3413/4000:  10%|█         | 1/10 [00:00<00:04,  1.93it/s]
+Epoch 3413/4000:  40%|████      | 4/10 [00:00<00:00,  7.19it/s]
+Epoch 3413/4000:  70%|███████   | 7/10 [00:00<00:00, 11.45it/s]
+Epoch 3413/4000: 100%|██████████| 10/10 [00:00<00:00, 14.57it/s]
+Epoch 3413/4000: 100%|██████████| 10/10 [00:01<00:00,  9.51it/s]
+epoch: 3412, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309557, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3414/4000:  10%|█         | 1/10 [00:00<00:04,  1.95it/s]
+Epoch 3414/4000:  30%|███       | 3/10 [00:00<00:01,  5.87it/s]
+Epoch 3414/4000:  50%|█████     | 5/10 [00:01<00:00,  5.01it/s]
+Epoch 3414/4000:  80%|████████  | 8/10 [00:01<00:00,  8.52it/s]
+Epoch 3414/4000: 100%|██████████| 10/10 [00:01<00:00,  7.08it/s]
+epoch: 3413, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309554, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3415/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3415/4000:  10%|█         | 1/10 [00:00<00:03,  2.26it/s]
+Epoch 3415/4000:  30%|███       | 3/10 [00:00<00:01,  6.39it/s]
+Epoch 3415/4000:  50%|█████     | 5/10 [00:01<00:00,  5.00it/s]
+Epoch 3415/4000:  80%|████████  | 8/10 [00:01<00:00,  8.55it/s]
+Epoch 3415/4000: 100%|██████████| 10/10 [00:01<00:00,  7.31it/s]
+epoch: 3414, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309550, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3416/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3416/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 3416/4000:  40%|████      | 4/10 [00:01<00:01,  4.02it/s]
+Epoch 3416/4000:  70%|███████   | 7/10 [00:01<00:00,  7.41it/s]
+Epoch 3416/4000: 100%|██████████| 10/10 [00:01<00:00, 10.81it/s]
+Epoch 3416/4000: 100%|██████████| 10/10 [00:01<00:00,  6.95it/s]
+epoch: 3415, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309552, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3417/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3417/4000:  10%|█         | 1/10 [00:00<00:04,  2.05it/s]
+Epoch 3417/4000:  40%|████      | 4/10 [00:00<00:00,  7.54it/s]
+Epoch 3417/4000:  60%|██████    | 6/10 [00:01<00:00,  5.75it/s]
+Epoch 3417/4000:  90%|█████████ | 9/10 [00:01<00:00,  9.29it/s]
+Epoch 3417/4000: 100%|██████████| 10/10 [00:01<00:00,  7.32it/s]
+epoch: 3416, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309577, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3418/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3418/4000:  40%|████      | 4/10 [00:01<00:01,  4.00it/s]
+Epoch 3418/4000:  70%|███████   | 7/10 [00:01<00:00,  7.23it/s]
+Epoch 3418/4000: 100%|██████████| 10/10 [00:01<00:00, 10.29it/s]
+Epoch 3418/4000: 100%|██████████| 10/10 [00:01<00:00,  6.72it/s]
+epoch: 3417, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309588, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3419/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3419/4000:  10%|█         | 1/10 [00:00<00:05,  1.78it/s]
+Epoch 3419/4000:  40%|████      | 4/10 [00:00<00:00,  7.01it/s]
+Epoch 3419/4000:  60%|██████    | 6/10 [00:01<00:00,  5.72it/s]
+Epoch 3419/4000:  90%|█████████ | 9/10 [00:01<00:00,  9.01it/s]
+Epoch 3419/4000: 100%|██████████| 10/10 [00:01<00:00,  7.00it/s]
+epoch: 3418, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309609, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3420/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3420/4000:  10%|█         | 1/10 [00:00<00:05,  1.76it/s]
+Epoch 3420/4000:  40%|████      | 4/10 [00:00<00:00,  6.96it/s]
+Epoch 3420/4000:  70%|███████   | 7/10 [00:00<00:00, 11.53it/s]
+Epoch 3420/4000: 100%|██████████| 10/10 [00:00<00:00, 15.00it/s]
+Epoch 3420/4000: 100%|██████████| 10/10 [00:01<00:00,  9.32it/s]
+Learning rate updated: 2.0050189330723186e-07
+epoch: 3419, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309627, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3421/4000:  40%|████      | 4/10 [00:00<00:00,  6.83it/s]
+Epoch 3421/4000:  70%|███████   | 7/10 [00:00<00:00, 11.59it/s]
+Epoch 3421/4000: 100%|██████████| 10/10 [00:00<00:00, 15.37it/s]
+Epoch 3421/4000: 100%|██████████| 10/10 [00:01<00:00,  9.51it/s]
+epoch: 3420, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309628, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3422/4000:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3422/4000:  30%|███       | 3/10 [00:00<00:01,  6.22it/s]
+Epoch 3422/4000:  60%|██████    | 6/10 [00:00<00:00, 11.34it/s]
+Epoch 3422/4000:  90%|█████████ | 9/10 [00:00<00:00, 15.21it/s]
+Epoch 3422/4000: 100%|██████████| 10/10 [00:00<00:00, 10.10it/s]
+epoch: 3421, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309627, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3423/4000:  40%|████      | 4/10 [00:00<00:00,  6.80it/s]
+Epoch 3423/4000:  70%|███████   | 7/10 [00:00<00:00, 11.15it/s]
+Epoch 3423/4000: 100%|██████████| 10/10 [00:00<00:00, 14.48it/s]
+Epoch 3423/4000: 100%|██████████| 10/10 [00:01<00:00,  9.15it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3424/4000:  30%|███       | 3/10 [00:00<00:01,  5.35it/s]
+Epoch 3424/4000:  60%|██████    | 6/10 [00:00<00:00,  9.95it/s]
+Epoch 3424/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.83it/s]
+Epoch 3424/4000: 100%|██████████| 10/10 [00:01<00:00,  9.09it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3425/4000:  70%|███████   | 7/10 [00:00<00:00, 10.80it/s]
+Epoch 3425/4000: 100%|██████████| 10/10 [00:01<00:00, 14.38it/s]
+Epoch 3425/4000: 100%|██████████| 10/10 [00:01<00:00,  8.64it/s]
+epoch: 3424, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309634, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3426/4000:  40%|████      | 4/10 [00:00<00:00,  6.78it/s]
+Epoch 3426/4000:  70%|███████   | 7/10 [00:00<00:00, 11.36it/s]
+Epoch 3426/4000: 100%|██████████| 10/10 [00:00<00:00, 14.95it/s]
+Epoch 3426/4000: 100%|██████████| 10/10 [00:01<00:00,  9.31it/s]
+epoch: 3425, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309615, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3427/4000:  10%|█         | 1/10 [00:00<00:04,  1.81it/s]
+Epoch 3427/4000:  30%|███       | 3/10 [00:00<00:01,  5.51it/s]
+Epoch 3427/4000:  60%|██████    | 6/10 [00:00<00:00, 10.28it/s]
+Epoch 3427/4000:  90%|█████████ | 9/10 [00:00<00:00, 13.78it/s]
+Epoch 3427/4000: 100%|██████████| 10/10 [00:01<00:00,  9.18it/s]
+epoch: 3426, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309594, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3428/4000: 100%|██████████| 10/10 [00:00<00:00, 15.35it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3429/4000: 100%|██████████| 10/10 [00:00<00:00, 14.45it/s]
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+epoch: 3428, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309555, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3430/4000:  70%|███████   | 7/10 [00:00<00:00, 11.06it/s]
+Epoch 3430/4000: 100%|██████████| 10/10 [00:00<00:00, 14.45it/s]
+Epoch 3430/4000: 100%|██████████| 10/10 [00:01<00:00,  9.02it/s]
+epoch: 3429, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309568, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3431/4000:  70%|███████   | 7/10 [00:00<00:00, 11.76it/s]
+Epoch 3431/4000: 100%|██████████| 10/10 [00:00<00:00, 15.06it/s]
+Epoch 3431/4000: 100%|██████████| 10/10 [00:01<00:00,  9.36it/s]
+Learning rate updated: 1.9047679864187027e-07
+epoch: 3430, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309595, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3432/4000: 100%|██████████| 10/10 [00:01<00:00, 10.40it/s]
+Epoch 3432/4000: 100%|██████████| 10/10 [00:01<00:00,  6.71it/s]
+epoch: 3431, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309606, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3433/4000:  90%|█████████ | 9/10 [00:01<00:00,  7.32it/s]
+Epoch 3433/4000: 100%|██████████| 10/10 [00:01<00:00,  5.99it/s]
+epoch: 3432, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.309598, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3434/4000:  90%|█████████ | 9/10 [00:01<00:00,  9.17it/s]
+Epoch 3434/4000: 100%|██████████| 10/10 [00:01<00:00,  7.32it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 3435/4000: 100%|██████████| 10/10 [00:01<00:00, 10.63it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]epoch: 3795, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.308607, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
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+Epoch 3997/4000:  60%|██████    | 6/10 [00:01<00:00,  6.35it/s]
+Epoch 3997/4000:  90%|█████████ | 9/10 [00:01<00:00,  9.67it/s]
+Epoch 3997/4000: 100%|██████████| 10/10 [00:01<00:00,  6.72it/s]
+epoch: 3996, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.308439, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3998/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3998/4000:  10%|█         | 1/10 [00:00<00:03,  2.29it/s]
+Epoch 3998/4000:  40%|████      | 4/10 [00:00<00:01,  4.32it/s]
+Epoch 3998/4000:  80%|████████  | 8/10 [00:01<00:00,  9.03it/s]
+Epoch 3998/4000: 100%|██████████| 10/10 [00:01<00:00,  7.56it/s]
+epoch: 3997, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.308428, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3999/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3999/4000:  10%|█         | 1/10 [00:00<00:04,  2.02it/s]
+Epoch 3999/4000:  40%|████      | 4/10 [00:01<00:01,  3.99it/s]
+Epoch 3999/4000:  70%|███████   | 7/10 [00:01<00:00,  7.36it/s]
+Epoch 3999/4000: 100%|██████████| 10/10 [00:01<00:00, 10.76it/s]
+Epoch 3999/4000: 100%|██████████| 10/10 [00:01<00:00,  7.02it/s]
+epoch: 3998, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.308412, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 4000/4000:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 4000/4000:  10%|█         | 1/10 [00:00<00:03,  2.29it/s]
+Epoch 4000/4000:  40%|████      | 4/10 [00:01<00:01,  4.23it/s]
+Epoch 4000/4000:  70%|███████   | 7/10 [00:01<00:00,  7.77it/s]
+Epoch 4000/4000: 100%|██████████| 10/10 [00:01<00:00, 11.38it/s]
+Epoch 4000/4000: 100%|██████████| 10/10 [00:01<00:00,  7.43it/s]
+epoch: 3999, beta = 0.000008, Train MSE: 0.000003, Train CE:0.000000, Train KL:3.308411, Val MSE:0.000003, Val CE:0.000000, Train ACC:1.000000, Val ACC:1.000000
+Training time: 76.4546 mins
+Successfully load and save the model!
+Successfully save pretrained embeddings in disk!
+[TabSyn] Step 2/2: Training diffusion model
+/opt/conda/lib/python3.11/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
+  import pynvml  # type: ignore[import]
+/workspace/tabsyn/tabsyn/ckpt/tabsyn_c20/
+MLPDiffusion(
+  (proj): Linear(in_features=28, out_features=1024, bias=True)
+  (mlp): Sequential(
+    (0): Linear(in_features=1024, out_features=2048, bias=True)
+    (1): SiLU()
+    (2): Linear(in_features=2048, out_features=2048, bias=True)
+    (3): SiLU()
+    (4): Linear(in_features=2048, out_features=1024, bias=True)
+    (5): SiLU()
+    (6): Linear(in_features=1024, out_features=28, bias=True)
+  )
+  (map_noise): PositionalEmbedding()
+  (time_embed): Sequential(
+    (0): Linear(in_features=1024, out_features=1024, bias=True)
+    (1): SiLU()
+    (2): Linear(in_features=1024, out_features=1024, bias=True)
+  )
+)
+the number of parameters 10551324
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 1/10001:   0%|          | 0/10 [00:01<?, ?it/s, Loss=0.842]
+Epoch 1/10001:  10%|█         | 1/10 [00:01<00:14,  1.60s/it, Loss=0.842]
+Epoch 1/10001:  10%|█         | 1/10 [00:01<00:14,  1.60s/it, Loss=0.808]
+Epoch 1/10001:  10%|█         | 1/10 [00:01<00:14,  1.60s/it, Loss=0.795]
+Epoch 1/10001:  10%|█         | 1/10 [00:01<00:14,  1.60s/it, Loss=0.757]
+Epoch 1/10001:  10%|█         | 1/10 [00:01<00:14,  1.60s/it, Loss=0.723]
+Epoch 1/10001:  10%|█         | 1/10 [00:01<00:14,  1.60s/it, Loss=0.711]
+Epoch 1/10001:  60%|██████    | 6/10 [00:01<00:00,  4.59it/s, Loss=0.711]
+Epoch 1/10001:  60%|██████    | 6/10 [00:01<00:00,  4.59it/s, Loss=0.713]
+Epoch 1/10001:  60%|██████    | 6/10 [00:01<00:00,  4.59it/s, Loss=0.71] 
+Epoch 1/10001:  60%|██████    | 6/10 [00:01<00:00,  4.59it/s, Loss=0.717]
+Epoch 1/10001:  60%|██████    | 6/10 [00:01<00:00,  4.59it/s, Loss=0.691]
+Epoch 1/10001: 100%|██████████| 10/10 [00:01<00:00,  5.34it/s, Loss=0.691]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 2/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.69]
+Epoch 2/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.69]
+Epoch 2/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.685]
+Epoch 2/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.68] 
+Epoch 2/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.68]
+Epoch 2/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.682]
+Epoch 2/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.675]
+Epoch 2/10001:  60%|██████    | 6/10 [00:00<00:00, 13.40it/s, Loss=0.675]
+Epoch 2/10001:  60%|██████    | 6/10 [00:00<00:00, 13.40it/s, Loss=0.677]
+Epoch 2/10001:  60%|██████    | 6/10 [00:00<00:00, 13.40it/s, Loss=0.671]
+Epoch 2/10001:  60%|██████    | 6/10 [00:00<00:00, 13.40it/s, Loss=0.656]
+Epoch 2/10001:  60%|██████    | 6/10 [00:00<00:00, 13.40it/s, Loss=0.649]
+Epoch 2/10001: 100%|██████████| 10/10 [00:00<00:00, 12.98it/s, Loss=0.649]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 3/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.644]
+Epoch 3/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.644]
+Epoch 3/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.641]
+Epoch 3/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.62] 
+Epoch 3/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.605]
+Epoch 3/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.603]
+Epoch 3/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.727]
+Epoch 3/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.727]
+Epoch 3/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.713]
+Epoch 3/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.774]
+Epoch 3/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.716]
+Epoch 3/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.699]
+Epoch 3/10001: 100%|██████████| 10/10 [00:00<00:00, 19.29it/s, Loss=0.699]
+Epoch 3/10001: 100%|██████████| 10/10 [00:00<00:00, 12.39it/s, Loss=0.699]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 4/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 4/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.693]
+Epoch 4/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.693]
+Epoch 4/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.653]
+Epoch 4/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.637]
+Epoch 4/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.642]
+Epoch 4/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.632]
+Epoch 4/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.623]
+Epoch 4/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.623]
+Epoch 4/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.601]
+Epoch 4/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.594]
+Epoch 4/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.587]
+Epoch 4/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.572]
+Epoch 4/10001: 100%|██████████| 10/10 [00:00<00:00, 12.39it/s, Loss=0.572]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 5/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 5/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.569]
+Epoch 5/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.569]
+Epoch 5/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.565]
+Epoch 5/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.559]
+Epoch 5/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.554]
+Epoch 5/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.57] 
+Epoch 5/10001:  50%|█████     | 5/10 [00:00<00:00,  9.44it/s, Loss=0.57]
+Epoch 5/10001:  50%|█████     | 5/10 [00:00<00:00,  9.44it/s, Loss=0.586]
+Epoch 5/10001:  50%|█████     | 5/10 [00:00<00:00,  9.44it/s, Loss=0.557]
+Epoch 5/10001:  50%|█████     | 5/10 [00:00<00:00,  9.44it/s, Loss=0.545]
+Epoch 5/10001:  50%|█████     | 5/10 [00:00<00:00,  9.44it/s, Loss=0.541]
+Epoch 5/10001:  90%|█████████ | 9/10 [00:00<00:00, 15.58it/s, Loss=0.541]
+Epoch 5/10001:  90%|█████████ | 9/10 [00:00<00:00, 15.58it/s, Loss=0.535]
+Epoch 5/10001: 100%|██████████| 10/10 [00:00<00:00, 10.37it/s, Loss=0.535]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 6/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 6/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.526]
+Epoch 6/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.526]
+Epoch 6/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.515]
+Epoch 6/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.51] 
+Epoch 6/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.511]
+Epoch 6/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.508]
+Epoch 6/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.501]
+Epoch 6/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.499]
+Epoch 6/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.493]
+Epoch 6/10001:  80%|████████  | 8/10 [00:00<00:00, 18.02it/s, Loss=0.493]
+Epoch 6/10001:  80%|████████  | 8/10 [00:00<00:00, 18.02it/s, Loss=0.483]
+Epoch 6/10001:  80%|████████  | 8/10 [00:00<00:00, 18.02it/s, Loss=0.491]
+Epoch 6/10001: 100%|██████████| 10/10 [00:00<00:00, 14.25it/s, Loss=0.491]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 7/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 7/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.481]
+Epoch 7/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.481]
+Epoch 7/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.48] 
+Epoch 7/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.473]
+Epoch 7/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.47] 
+Epoch 7/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.469]
+Epoch 7/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.467]
+Epoch 7/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.462]
+Epoch 7/10001:  70%|███████   | 7/10 [00:00<00:00, 16.50it/s, Loss=0.462]
+Epoch 7/10001:  70%|███████   | 7/10 [00:00<00:00, 16.50it/s, Loss=0.454]
+Epoch 7/10001:  70%|███████   | 7/10 [00:00<00:00, 16.50it/s, Loss=0.456]
+Epoch 7/10001:  70%|███████   | 7/10 [00:00<00:00, 16.50it/s, Loss=0.446]
+Epoch 7/10001: 100%|██████████| 10/10 [00:00<00:00, 14.53it/s, Loss=0.446]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 8/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 8/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.459]
+Epoch 8/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.459]
+Epoch 8/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.452]
+Epoch 8/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.462]
+Epoch 8/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.454]
+Epoch 8/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.459]
+Epoch 8/10001:  50%|█████     | 5/10 [00:00<00:00, 11.75it/s, Loss=0.459]
+Epoch 8/10001:  50%|█████     | 5/10 [00:00<00:00, 11.75it/s, Loss=0.443]
+Epoch 8/10001:  50%|█████     | 5/10 [00:00<00:00, 11.75it/s, Loss=0.446]
+Epoch 8/10001:  50%|█████     | 5/10 [00:00<00:00, 11.75it/s, Loss=0.443]
+Epoch 8/10001:  50%|█████     | 5/10 [00:00<00:00, 11.75it/s, Loss=0.44] 
+Epoch 8/10001:  50%|█████     | 5/10 [00:00<00:00, 11.75it/s, Loss=0.435]
+Epoch 8/10001: 100%|██████████| 10/10 [00:00<00:00, 20.66it/s, Loss=0.435]
+Epoch 8/10001: 100%|██████████| 10/10 [00:00<00:00, 13.13it/s, Loss=0.435]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 9/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 9/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.44]
+Epoch 9/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.44]
+Epoch 9/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.438]
+Epoch 9/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.429]
+Epoch 9/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.426]
+Epoch 9/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.424]
+Epoch 9/10001:  50%|█████     | 5/10 [00:00<00:00, 11.04it/s, Loss=0.424]
+Epoch 9/10001:  50%|█████     | 5/10 [00:00<00:00, 11.04it/s, Loss=0.423]
+Epoch 9/10001:  50%|█████     | 5/10 [00:00<00:00, 11.04it/s, Loss=0.426]
+Epoch 9/10001:  50%|█████     | 5/10 [00:00<00:00, 11.04it/s, Loss=0.423]
+Epoch 9/10001:  50%|█████     | 5/10 [00:00<00:00, 11.04it/s, Loss=0.418]
+Epoch 9/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.03it/s, Loss=0.418]
+Epoch 9/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.03it/s, Loss=0.417]
+Epoch 9/10001: 100%|██████████| 10/10 [00:00<00:00, 12.34it/s, Loss=0.417]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 10/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 10/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.415]
+Epoch 10/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.415]
+Epoch 10/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.412]
+Epoch 10/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.411]
+Epoch 10/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.408]
+Epoch 10/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.411]
+Epoch 10/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.411]
+Epoch 10/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.412]
+Epoch 10/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.413]
+Epoch 10/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.412]
+Epoch 10/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.413]
+Epoch 10/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.411]
+Epoch 10/10001: 100%|██████████| 10/10 [00:00<00:00, 20.63it/s, Loss=0.411]
+Epoch 10/10001: 100%|██████████| 10/10 [00:00<00:00, 13.03it/s, Loss=0.411]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 11/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 11/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.403]
+Epoch 11/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.403]
+Epoch 11/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.399]
+Epoch 11/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.398]
+Epoch 11/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.399]
+Epoch 11/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.399]
+Epoch 11/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.397]
+Epoch 11/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.397]
+Epoch 11/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.393]
+Epoch 11/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.394]
+Epoch 11/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.388]
+Epoch 11/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.392]
+Epoch 11/10001: 100%|██████████| 10/10 [00:00<00:00, 13.39it/s, Loss=0.392]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 12/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 12/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.391]
+Epoch 12/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.391]
+Epoch 12/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.39] 
+Epoch 12/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.385]
+Epoch 12/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.383]
+Epoch 12/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.381]
+Epoch 12/10001:  50%|█████     | 5/10 [00:00<00:00, 11.62it/s, Loss=0.381]
+Epoch 12/10001:  50%|█████     | 5/10 [00:00<00:00, 11.62it/s, Loss=0.376]
+Epoch 12/10001:  50%|█████     | 5/10 [00:00<00:00, 11.62it/s, Loss=0.379]
+Epoch 12/10001:  50%|█████     | 5/10 [00:00<00:00, 11.62it/s, Loss=0.377]
+Epoch 12/10001:  50%|█████     | 5/10 [00:00<00:00, 11.62it/s, Loss=0.374]
+Epoch 12/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.71it/s, Loss=0.374]
+Epoch 12/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.71it/s, Loss=0.38] 
+Epoch 12/10001: 100%|██████████| 10/10 [00:00<00:00, 12.86it/s, Loss=0.38]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 13/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 13/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.381]
+Epoch 13/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.381]
+Epoch 13/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.378]
+Epoch 13/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.389]
+Epoch 13/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.383]
+Epoch 13/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.374]
+Epoch 13/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.374]
+Epoch 13/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.377]
+Epoch 13/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.372]
+Epoch 13/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.373]
+Epoch 13/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.376]
+Epoch 13/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.379]
+Epoch 13/10001: 100%|██████████| 10/10 [00:00<00:00, 13.11it/s, Loss=0.379]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 14/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 14/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.38]
+Epoch 14/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.38]
+Epoch 14/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.376]
+Epoch 14/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.371]
+Epoch 14/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.372]
+Epoch 14/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.37] 
+Epoch 14/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.367]
+Epoch 14/10001:  60%|██████    | 6/10 [00:00<00:00, 14.59it/s, Loss=0.367]
+Epoch 14/10001:  60%|██████    | 6/10 [00:00<00:00, 14.59it/s, Loss=0.369]
+Epoch 14/10001:  60%|██████    | 6/10 [00:00<00:00, 14.59it/s, Loss=0.375]
+Epoch 14/10001:  60%|██████    | 6/10 [00:00<00:00, 14.59it/s, Loss=0.37] 
+Epoch 14/10001:  60%|██████    | 6/10 [00:00<00:00, 14.59it/s, Loss=0.365]
+Epoch 14/10001: 100%|██████████| 10/10 [00:00<00:00, 14.81it/s, Loss=0.365]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 15/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 15/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.361]
+Epoch 15/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.361]
+Epoch 15/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.358]
+Epoch 15/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.365]
+Epoch 15/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.353]
+Epoch 15/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.361]
+Epoch 15/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.359]
+Epoch 15/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.359]
+Epoch 15/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.366]
+Epoch 15/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.358]
+Epoch 15/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.357]
+Epoch 15/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.364]
+Epoch 15/10001: 100%|██████████| 10/10 [00:00<00:00, 20.29it/s, Loss=0.364]
+Epoch 15/10001: 100%|██████████| 10/10 [00:00<00:00, 13.34it/s, Loss=0.364]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 16/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 16/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.361]
+Epoch 16/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.361]
+Epoch 16/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.357]
+Epoch 16/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.361]
+Epoch 16/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.358]
+Epoch 16/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.361]
+Epoch 16/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.358]
+Epoch 16/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.358]
+Epoch 16/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.35] 
+Epoch 16/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.351]
+Epoch 16/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.358]
+Epoch 16/10001:  60%|██████    | 6/10 [00:00<00:00, 14.08it/s, Loss=0.349]
+Epoch 16/10001: 100%|██████████| 10/10 [00:00<00:00, 13.97it/s, Loss=0.349]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 17/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 17/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.362]
+Epoch 17/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.362]
+Epoch 17/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.351]
+Epoch 17/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.348]
+Epoch 17/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.35] 
+Epoch 17/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.352]
+Epoch 17/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.352]
+Epoch 17/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.355]
+Epoch 17/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.346]
+Epoch 17/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.349]
+Epoch 17/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.45it/s, Loss=0.349]
+Epoch 17/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.45it/s, Loss=0.356]
+Epoch 17/10001: 100%|██████████| 10/10 [00:00<00:00, 14.01it/s, Loss=0.356]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 18/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 18/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.345]
+Epoch 18/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.345]
+Epoch 18/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.353]
+Epoch 18/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.346]
+Epoch 18/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.346]
+Epoch 18/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.344]
+Epoch 18/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.343]
+Epoch 18/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.34] 
+Epoch 18/10001:  70%|███████   | 7/10 [00:00<00:00, 16.37it/s, Loss=0.34]
+Epoch 18/10001:  70%|███████   | 7/10 [00:00<00:00, 16.37it/s, Loss=0.342]
+Epoch 18/10001:  70%|███████   | 7/10 [00:00<00:00, 16.37it/s, Loss=0.344]
+Epoch 18/10001:  70%|███████   | 7/10 [00:00<00:00, 16.37it/s, Loss=0.348]
+Epoch 18/10001: 100%|██████████| 10/10 [00:00<00:00, 14.59it/s, Loss=0.348]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 19/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 19/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.344]
+Epoch 19/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.344]
+Epoch 19/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.343]
+Epoch 19/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.351]
+Epoch 19/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.339]
+Epoch 19/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.348]
+Epoch 19/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.354]
+Epoch 19/10001:  60%|██████    | 6/10 [00:00<00:00, 13.46it/s, Loss=0.354]
+Epoch 19/10001:  60%|██████    | 6/10 [00:00<00:00, 13.46it/s, Loss=0.348]
+Epoch 19/10001:  60%|██████    | 6/10 [00:00<00:00, 13.46it/s, Loss=0.344]
+Epoch 19/10001:  60%|██████    | 6/10 [00:00<00:00, 13.46it/s, Loss=0.345]
+Epoch 19/10001:  60%|██████    | 6/10 [00:00<00:00, 13.46it/s, Loss=0.331]
+Epoch 19/10001: 100%|██████████| 10/10 [00:00<00:00, 13.38it/s, Loss=0.331]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 20/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 20/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.338]
+Epoch 20/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.338]
+Epoch 20/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.34] 
+Epoch 20/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.338]
+Epoch 20/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.339]
+Epoch 20/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.34] 
+Epoch 20/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.336]
+Epoch 20/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.344]
+Epoch 20/10001:  70%|███████   | 7/10 [00:00<00:00, 20.54it/s, Loss=0.344]
+Epoch 20/10001:  70%|███████   | 7/10 [00:00<00:00, 20.54it/s, Loss=0.342]
+Epoch 20/10001:  70%|███████   | 7/10 [00:00<00:00, 20.54it/s, Loss=0.337]
+Epoch 20/10001:  70%|███████   | 7/10 [00:00<00:00, 20.54it/s, Loss=0.343]
+Epoch 20/10001: 100%|██████████| 10/10 [00:00<00:00, 17.79it/s, Loss=0.343]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 21/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 21/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.34]
+Epoch 21/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.34]
+Epoch 21/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.333]
+Epoch 21/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.339]
+Epoch 21/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.341]
+Epoch 21/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.335]
+Epoch 21/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.328]
+Epoch 21/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.333]
+Epoch 21/10001:  70%|███████   | 7/10 [00:00<00:00, 16.70it/s, Loss=0.333]
+Epoch 21/10001:  70%|███████   | 7/10 [00:00<00:00, 16.70it/s, Loss=0.333]
+Epoch 21/10001:  70%|███████   | 7/10 [00:00<00:00, 16.70it/s, Loss=0.334]
+Epoch 21/10001:  70%|███████   | 7/10 [00:00<00:00, 16.70it/s, Loss=0.33] 
+Epoch 21/10001: 100%|██████████| 10/10 [00:00<00:00, 14.30it/s, Loss=0.33]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 22/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 22/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.329]
+Epoch 22/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.329]
+Epoch 22/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.326]
+Epoch 22/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.326]
+Epoch 22/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.33] 
+Epoch 22/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.333]
+Epoch 22/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.334]
+Epoch 22/10001:  60%|██████    | 6/10 [00:00<00:00, 13.68it/s, Loss=0.334]
+Epoch 22/10001:  60%|██████    | 6/10 [00:00<00:00, 13.68it/s, Loss=0.324]
+Epoch 22/10001:  60%|██████    | 6/10 [00:00<00:00, 13.68it/s, Loss=0.327]
+Epoch 22/10001:  60%|██████    | 6/10 [00:00<00:00, 13.68it/s, Loss=0.334]
+Epoch 22/10001:  60%|██████    | 6/10 [00:00<00:00, 13.68it/s, Loss=0.334]
+Epoch 22/10001: 100%|██████████| 10/10 [00:00<00:00, 13.65it/s, Loss=0.334]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 23/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 23/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.329]
+Epoch 23/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.329]
+Epoch 23/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.324]
+Epoch 23/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.329]
+Epoch 23/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.324]
+Epoch 23/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.321]
+Epoch 23/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.327]
+Epoch 23/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.329]
+Epoch 23/10001:  70%|███████   | 7/10 [00:00<00:00, 16.98it/s, Loss=0.329]
+Epoch 23/10001:  70%|███████   | 7/10 [00:00<00:00, 16.98it/s, Loss=0.324]
+Epoch 23/10001:  70%|███████   | 7/10 [00:00<00:00, 16.98it/s, Loss=0.33] 
+Epoch 23/10001:  70%|███████   | 7/10 [00:00<00:00, 16.98it/s, Loss=0.321]
+Epoch 23/10001: 100%|██████████| 10/10 [00:00<00:00, 14.69it/s, Loss=0.321]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 24/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 24/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.325]
+Epoch 24/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.325]
+Epoch 24/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.323]
+Epoch 24/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.326]
+Epoch 24/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.329]
+Epoch 24/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.33] 
+Epoch 24/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.328]
+Epoch 24/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.328]
+Epoch 24/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.318]
+Epoch 24/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.323]
+Epoch 24/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.327]
+Epoch 24/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.322]
+Epoch 24/10001: 100%|██████████| 10/10 [00:00<00:00, 13.77it/s, Loss=0.322]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 25/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 25/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.313]
+Epoch 25/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.313]
+Epoch 25/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.318]
+Epoch 25/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.323]
+Epoch 25/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.329]
+Epoch 25/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.321]
+Epoch 25/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.321]
+Epoch 25/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.315]
+Epoch 25/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.322]
+Epoch 25/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.328]
+Epoch 25/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.316]
+Epoch 25/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.319]
+Epoch 25/10001: 100%|██████████| 10/10 [00:00<00:00, 13.29it/s, Loss=0.319]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 26/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 26/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.313]
+Epoch 26/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.313]
+Epoch 26/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.324]
+Epoch 26/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.314]
+Epoch 26/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.321]
+Epoch 26/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.316]
+Epoch 26/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.318]
+Epoch 26/10001:  60%|██████    | 6/10 [00:00<00:00, 14.37it/s, Loss=0.318]
+Epoch 26/10001:  60%|██████    | 6/10 [00:00<00:00, 14.37it/s, Loss=0.317]
+Epoch 26/10001:  60%|██████    | 6/10 [00:00<00:00, 14.37it/s, Loss=0.324]
+Epoch 26/10001:  60%|██████    | 6/10 [00:00<00:00, 14.37it/s, Loss=0.317]
+Epoch 26/10001:  60%|██████    | 6/10 [00:00<00:00, 14.37it/s, Loss=0.315]
+Epoch 26/10001: 100%|██████████| 10/10 [00:00<00:00, 13.32it/s, Loss=0.315]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 27/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 27/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.312]
+Epoch 27/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.312]
+Epoch 27/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.315]
+Epoch 27/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.316]
+Epoch 27/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.313]
+Epoch 27/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.316]
+Epoch 27/10001:  50%|█████     | 5/10 [00:00<00:00, 11.36it/s, Loss=0.316]
+Epoch 27/10001:  50%|█████     | 5/10 [00:00<00:00, 11.36it/s, Loss=0.31] 
+Epoch 27/10001:  50%|█████     | 5/10 [00:00<00:00, 11.36it/s, Loss=0.314]
+Epoch 27/10001:  50%|█████     | 5/10 [00:00<00:00, 11.36it/s, Loss=0.317]
+Epoch 27/10001:  50%|█████     | 5/10 [00:00<00:00, 11.36it/s, Loss=0.313]
+Epoch 27/10001:  50%|█████     | 5/10 [00:00<00:00, 11.36it/s, Loss=0.311]
+Epoch 27/10001: 100%|██████████| 10/10 [00:00<00:00, 20.49it/s, Loss=0.311]
+Epoch 27/10001: 100%|██████████| 10/10 [00:00<00:00, 12.93it/s, Loss=0.311]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 28/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 28/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.313]
+Epoch 28/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.313]
+Epoch 28/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.308]
+Epoch 28/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.313]
+Epoch 28/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.309]
+Epoch 28/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.309]
+Epoch 28/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.309]
+Epoch 28/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.316]
+Epoch 28/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.309]
+Epoch 28/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.311]
+Epoch 28/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.306]
+Epoch 28/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.66it/s, Loss=0.306]
+Epoch 28/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.66it/s, Loss=0.31] 
+Epoch 28/10001: 100%|██████████| 10/10 [00:00<00:00, 12.44it/s, Loss=0.31]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 29/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 29/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.313]
+Epoch 29/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.313]
+Epoch 29/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.31] 
+Epoch 29/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.317]
+Epoch 29/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.312]
+Epoch 29/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.315]
+Epoch 29/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.311]
+Epoch 29/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.302]
+Epoch 29/10001:  70%|███████   | 7/10 [00:00<00:00, 16.52it/s, Loss=0.302]
+Epoch 29/10001:  70%|███████   | 7/10 [00:00<00:00, 16.52it/s, Loss=0.316]
+Epoch 29/10001:  70%|███████   | 7/10 [00:00<00:00, 16.52it/s, Loss=0.311]
+Epoch 29/10001:  70%|███████   | 7/10 [00:00<00:00, 16.52it/s, Loss=0.31] 
+Epoch 29/10001: 100%|██████████| 10/10 [00:00<00:00, 14.17it/s, Loss=0.31]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 30/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 30/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.31]
+Epoch 30/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.31]
+Epoch 30/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.312]
+Epoch 30/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.308]
+Epoch 30/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.31] 
+Epoch 30/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.308]
+Epoch 30/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.313]
+Epoch 30/10001:  60%|██████    | 6/10 [00:00<00:00, 14.24it/s, Loss=0.313]
+Epoch 30/10001:  60%|██████    | 6/10 [00:00<00:00, 14.24it/s, Loss=0.316]
+Epoch 30/10001:  60%|██████    | 6/10 [00:00<00:00, 14.24it/s, Loss=0.308]
+Epoch 30/10001:  60%|██████    | 6/10 [00:00<00:00, 14.24it/s, Loss=0.314]
+Epoch 30/10001:  60%|██████    | 6/10 [00:00<00:00, 14.24it/s, Loss=0.309]
+Epoch 30/10001: 100%|██████████| 10/10 [00:00<00:00, 14.13it/s, Loss=0.309]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 31/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 31/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.309]
+Epoch 31/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.309]
+Epoch 31/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.298]
+Epoch 31/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.31] 
+Epoch 31/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.306]
+Epoch 31/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.306]
+Epoch 31/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.306]
+Epoch 31/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.304]
+Epoch 31/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.305]
+Epoch 31/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.303]
+Epoch 31/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.306]
+Epoch 31/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.69it/s, Loss=0.306]
+Epoch 31/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.69it/s, Loss=0.305]
+Epoch 31/10001: 100%|██████████| 10/10 [00:00<00:00, 12.50it/s, Loss=0.305]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 32/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 32/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.312]
+Epoch 32/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.312]
+Epoch 32/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.31] 
+Epoch 32/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.299]
+Epoch 32/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.307]
+Epoch 32/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.3]  
+Epoch 32/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.312]
+Epoch 32/10001:  60%|██████    | 6/10 [00:00<00:00, 14.57it/s, Loss=0.312]
+Epoch 32/10001:  60%|██████    | 6/10 [00:00<00:00, 14.57it/s, Loss=0.302]
+Epoch 32/10001:  60%|██████    | 6/10 [00:00<00:00, 14.57it/s, Loss=0.303]
+Epoch 32/10001:  60%|██████    | 6/10 [00:00<00:00, 14.57it/s, Loss=0.303]
+Epoch 32/10001:  60%|██████    | 6/10 [00:00<00:00, 14.57it/s, Loss=0.305]
+Epoch 32/10001: 100%|██████████| 10/10 [00:00<00:00, 14.79it/s, Loss=0.305]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 33/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 33/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.304]
+Epoch 33/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.304]
+Epoch 33/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.307]
+Epoch 33/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.309]
+Epoch 33/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.307]
+Epoch 33/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.308]
+Epoch 33/10001:  50%|█████     | 5/10 [00:00<00:00, 11.63it/s, Loss=0.308]
+Epoch 33/10001:  50%|█████     | 5/10 [00:00<00:00, 11.63it/s, Loss=0.307]
+Epoch 33/10001:  50%|█████     | 5/10 [00:00<00:00, 11.63it/s, Loss=0.306]
+Epoch 33/10001:  50%|█████     | 5/10 [00:00<00:00, 11.63it/s, Loss=0.303]
+Epoch 33/10001:  50%|█████     | 5/10 [00:00<00:00, 11.63it/s, Loss=0.307]
+Epoch 33/10001:  50%|█████     | 5/10 [00:00<00:00, 11.63it/s, Loss=0.308]
+Epoch 33/10001: 100%|██████████| 10/10 [00:00<00:00, 21.10it/s, Loss=0.308]
+Epoch 33/10001: 100%|██████████| 10/10 [00:00<00:00, 13.27it/s, Loss=0.308]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 34/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 34/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.312]
+Epoch 34/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.312]
+Epoch 34/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.311]
+Epoch 34/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.308]
+Epoch 34/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.306]
+Epoch 34/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.311]
+Epoch 34/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.311]
+Epoch 34/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.309]
+Epoch 34/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.303]
+Epoch 34/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.302]
+Epoch 34/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.306]
+Epoch 34/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.09it/s, Loss=0.306]
+Epoch 34/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.09it/s, Loss=0.301]
+Epoch 34/10001: 100%|██████████| 10/10 [00:00<00:00, 12.58it/s, Loss=0.301]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 35/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 35/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.31]
+Epoch 35/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.31]
+Epoch 35/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.308]
+Epoch 35/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.309]
+Epoch 35/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.302]
+Epoch 35/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.307]
+Epoch 35/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.308]
+Epoch 35/10001:  60%|██████    | 6/10 [00:00<00:00, 16.54it/s, Loss=0.308]
+Epoch 35/10001:  60%|██████    | 6/10 [00:00<00:00, 16.54it/s, Loss=0.306]
+Epoch 35/10001:  60%|██████    | 6/10 [00:00<00:00, 16.54it/s, Loss=0.302]
+Epoch 35/10001:  60%|██████    | 6/10 [00:00<00:00, 16.54it/s, Loss=0.298]
+Epoch 35/10001:  60%|██████    | 6/10 [00:00<00:00, 16.54it/s, Loss=0.309]
+Epoch 35/10001: 100%|██████████| 10/10 [00:00<00:00, 15.98it/s, Loss=0.309]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 36/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 36/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.304]
+Epoch 36/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.304]
+Epoch 36/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.305]
+Epoch 36/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.304]
+Epoch 36/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.301]
+Epoch 36/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.301]
+Epoch 36/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.301]
+Epoch 36/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.301]
+Epoch 36/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.299]
+Epoch 36/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.299]
+Epoch 36/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.302]
+Epoch 36/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.304]
+Epoch 36/10001: 100%|██████████| 10/10 [00:00<00:00, 15.47it/s, Loss=0.304]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 37/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 37/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.314]
+Epoch 37/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.314]
+Epoch 37/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.317]
+Epoch 37/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.312]
+Epoch 37/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.303]
+Epoch 37/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.303]
+Epoch 37/10001:  50%|█████     | 5/10 [00:00<00:00, 11.07it/s, Loss=0.303]
+Epoch 37/10001:  50%|█████     | 5/10 [00:00<00:00, 11.07it/s, Loss=0.3]  
+Epoch 37/10001:  50%|█████     | 5/10 [00:00<00:00, 11.07it/s, Loss=0.304]
+Epoch 37/10001:  50%|█████     | 5/10 [00:00<00:00, 11.07it/s, Loss=0.304]
+Epoch 37/10001:  50%|█████     | 5/10 [00:00<00:00, 11.07it/s, Loss=0.308]
+Epoch 37/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.83it/s, Loss=0.308]
+Epoch 37/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.83it/s, Loss=0.299]
+Epoch 37/10001: 100%|██████████| 10/10 [00:00<00:00, 12.40it/s, Loss=0.299]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 38/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 38/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.311]
+Epoch 38/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.311]
+Epoch 38/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.31] 
+Epoch 38/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.306]
+Epoch 38/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.306]
+Epoch 38/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.301]
+Epoch 38/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.298]
+Epoch 38/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.298]
+Epoch 38/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.308]
+Epoch 38/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.304]
+Epoch 38/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.314]
+Epoch 38/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.305]
+Epoch 38/10001: 100%|██████████| 10/10 [00:00<00:00, 15.76it/s, Loss=0.305]
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 39/10001:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 39/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.301]
+Epoch 39/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.302]
+Epoch 39/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.299]
+Epoch 39/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.304]
+Epoch 39/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.302]
+Epoch 39/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.303]
+Epoch 39/10001:  60%|██████    | 6/10 [00:00<00:00, 16.81it/s, Loss=0.303]
+Epoch 39/10001:  60%|██████    | 6/10 [00:00<00:00, 16.81it/s, Loss=0.306]
+Epoch 39/10001:  60%|██████    | 6/10 [00:00<00:00, 16.81it/s, Loss=0.304]
+Epoch 39/10001:  60%|██████    | 6/10 [00:00<00:00, 16.81it/s, Loss=0.303]
+Epoch 39/10001:  60%|██████    | 6/10 [00:00<00:00, 16.81it/s, Loss=0.306]
+Epoch 39/10001: 100%|██████████| 10/10 [00:00<00:00, 16.60it/s, Loss=0.306]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 40/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 40/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.301]
+Epoch 40/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.301]
+Epoch 40/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.297]
+Epoch 40/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.305]
+Epoch 40/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.302]
+Epoch 40/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.304]
+Epoch 40/10001:  50%|█████     | 5/10 [00:00<00:00, 11.14it/s, Loss=0.304]
+Epoch 40/10001:  50%|█████     | 5/10 [00:00<00:00, 11.14it/s, Loss=0.301]
+Epoch 40/10001:  50%|█████     | 5/10 [00:00<00:00, 11.14it/s, Loss=0.297]
+Epoch 40/10001:  50%|█████     | 5/10 [00:00<00:00, 11.14it/s, Loss=0.298]
+Epoch 40/10001:  50%|█████     | 5/10 [00:00<00:00, 11.14it/s, Loss=0.296]
+Epoch 40/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.11it/s, Loss=0.296]
+Epoch 40/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.11it/s, Loss=0.3]  
+Epoch 40/10001: 100%|██████████| 10/10 [00:00<00:00, 12.81it/s, Loss=0.3]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 41/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 41/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.301]
+Epoch 41/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.301]
+Epoch 41/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.3]  
+Epoch 41/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.301]
+Epoch 41/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.3]  
+Epoch 41/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.299]
+Epoch 41/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.3]  
+Epoch 41/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.293]
+Epoch 41/10001:  70%|███████   | 7/10 [00:00<00:00, 16.42it/s, Loss=0.293]
+Epoch 41/10001:  70%|███████   | 7/10 [00:00<00:00, 16.42it/s, Loss=0.299]
+Epoch 41/10001:  70%|███████   | 7/10 [00:00<00:00, 16.42it/s, Loss=0.297]
+Epoch 41/10001:  70%|███████   | 7/10 [00:00<00:00, 16.42it/s, Loss=0.299]
+Epoch 41/10001: 100%|██████████| 10/10 [00:00<00:00, 14.48it/s, Loss=0.299]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 42/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 42/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.303]
+Epoch 42/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.303]
+Epoch 42/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.303]
+Epoch 42/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.292]
+Epoch 42/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.298]
+Epoch 42/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.294]
+Epoch 42/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.301]
+Epoch 42/10001:  60%|██████    | 6/10 [00:00<00:00, 14.27it/s, Loss=0.301]
+Epoch 42/10001:  60%|██████    | 6/10 [00:00<00:00, 14.27it/s, Loss=0.305]
+Epoch 42/10001:  60%|██████    | 6/10 [00:00<00:00, 14.27it/s, Loss=0.298]
+Epoch 42/10001:  60%|██████    | 6/10 [00:00<00:00, 14.27it/s, Loss=0.298]
+Epoch 42/10001:  60%|██████    | 6/10 [00:00<00:00, 14.27it/s, Loss=0.3]  
+Epoch 42/10001: 100%|██████████| 10/10 [00:00<00:00, 14.25it/s, Loss=0.3]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 43/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 43/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.301]
+Epoch 43/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.301]
+Epoch 43/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.299]
+Epoch 43/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.295]
+Epoch 43/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.296]
+Epoch 43/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.296]
+Epoch 43/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.292]
+Epoch 43/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.292]
+Epoch 43/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.297]
+Epoch 43/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.3]  
+Epoch 43/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.3]
+Epoch 43/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.301]
+Epoch 43/10001: 100%|██████████| 10/10 [00:00<00:00, 15.12it/s, Loss=0.301]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 44/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 44/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.3]
+Epoch 44/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.3]
+Epoch 44/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.29]
+Epoch 44/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.296]
+Epoch 44/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.3]  
+Epoch 44/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.3]
+Epoch 44/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.294]
+Epoch 44/10001:  60%|██████    | 6/10 [00:00<00:00, 14.26it/s, Loss=0.294]
+Epoch 44/10001:  60%|██████    | 6/10 [00:00<00:00, 14.26it/s, Loss=0.293]
+Epoch 44/10001:  60%|██████    | 6/10 [00:00<00:00, 14.26it/s, Loss=0.29] 
+Epoch 44/10001:  60%|██████    | 6/10 [00:00<00:00, 14.26it/s, Loss=0.291]
+Epoch 44/10001:  60%|██████    | 6/10 [00:00<00:00, 14.26it/s, Loss=0.294]
+Epoch 44/10001: 100%|██████████| 10/10 [00:00<00:00, 14.14it/s, Loss=0.294]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 45/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 45/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.293]
+Epoch 45/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.293]
+Epoch 45/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.298]
+Epoch 45/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.29] 
+Epoch 45/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.288]
+Epoch 45/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.296]
+Epoch 45/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.296]
+Epoch 45/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.295]
+Epoch 45/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.298]
+Epoch 45/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.293]
+Epoch 45/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.294]
+Epoch 45/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.287]
+Epoch 45/10001: 100%|██████████| 10/10 [00:00<00:00, 20.26it/s, Loss=0.287]
+Epoch 45/10001: 100%|██████████| 10/10 [00:00<00:00, 12.99it/s, Loss=0.287]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 46/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 46/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.29]
+Epoch 46/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.29]
+Epoch 46/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.302]
+Epoch 46/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.296]
+Epoch 46/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.295]
+Epoch 46/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.291]
+Epoch 46/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.301]
+Epoch 46/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.3]  
+Epoch 46/10001:  70%|███████   | 7/10 [00:00<00:00, 17.19it/s, Loss=0.3]
+Epoch 46/10001:  70%|███████   | 7/10 [00:00<00:00, 17.19it/s, Loss=0.298]
+Epoch 46/10001:  70%|███████   | 7/10 [00:00<00:00, 17.19it/s, Loss=0.291]
+Epoch 46/10001:  70%|███████   | 7/10 [00:00<00:00, 17.19it/s, Loss=0.295]
+Epoch 46/10001: 100%|██████████| 10/10 [00:00<00:00, 14.90it/s, Loss=0.295]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 47/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 47/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.296]
+Epoch 47/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.296]
+Epoch 47/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.288]
+Epoch 47/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.294]
+Epoch 47/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.296]
+Epoch 47/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.301]
+Epoch 47/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.301]
+Epoch 47/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.289]
+Epoch 47/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.294]
+Epoch 47/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.295]
+Epoch 47/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.291]
+Epoch 47/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.293]
+Epoch 47/10001: 100%|██████████| 10/10 [00:00<00:00, 22.18it/s, Loss=0.293]
+Epoch 47/10001: 100%|██████████| 10/10 [00:00<00:00, 14.15it/s, Loss=0.293]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 48/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.29]
+Epoch 48/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.29]
+Epoch 48/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.291]
+Epoch 48/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.291]
+Epoch 48/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.291]
+Epoch 48/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.286]
+Epoch 48/10001:  50%|█████     | 5/10 [00:00<00:00, 11.51it/s, Loss=0.286]
+Epoch 48/10001:  50%|█████     | 5/10 [00:00<00:00, 11.51it/s, Loss=0.293]
+Epoch 48/10001:  50%|█████     | 5/10 [00:00<00:00, 11.51it/s, Loss=0.295]
+Epoch 48/10001:  50%|█████     | 5/10 [00:00<00:00, 11.51it/s, Loss=0.293]
+Epoch 48/10001:  50%|█████     | 5/10 [00:00<00:00, 11.51it/s, Loss=0.303]
+Epoch 48/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.37it/s, Loss=0.303]
+Epoch 48/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.37it/s, Loss=0.296]
+Epoch 48/10001: 100%|██████████| 10/10 [00:00<00:00, 12.61it/s, Loss=0.296]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 49/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 49/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.3]
+Epoch 49/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.3]
+Epoch 49/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.298]
+Epoch 49/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.294]
+Epoch 49/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.293]
+Epoch 49/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.293]
+Epoch 49/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.293]
+Epoch 49/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.294]
+Epoch 49/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.291]
+Epoch 49/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.299]
+Epoch 49/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.299]
+Epoch 49/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.63it/s, Loss=0.299]
+Epoch 49/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.63it/s, Loss=0.296]
+Epoch 49/10001: 100%|██████████| 10/10 [00:00<00:00, 12.24it/s, Loss=0.296]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 50/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 50/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.295]
+Epoch 50/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.295]
+Epoch 50/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.292]
+Epoch 50/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.3]  
+Epoch 50/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.287]
+Epoch 50/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.299]
+Epoch 50/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.294]
+Epoch 50/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.294]
+Epoch 50/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.29] 
+Epoch 50/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.296]
+Epoch 50/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.3]  
+Epoch 50/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.292]
+Epoch 50/10001: 100%|██████████| 10/10 [00:00<00:00, 19.92it/s, Loss=0.292]
+Epoch 50/10001: 100%|██████████| 10/10 [00:00<00:00, 13.26it/s, Loss=0.292]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 51/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 51/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.291]
+Epoch 51/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.291]
+Epoch 51/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.291]
+Epoch 51/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.295]
+Epoch 51/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.285]
+Epoch 51/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.287]
+Epoch 51/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.29] 
+Epoch 51/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.29]
+Epoch 51/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.287]
+Epoch 51/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.284]
+Epoch 51/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.3]  
+Epoch 51/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.294]
+Epoch 51/10001: 100%|██████████| 10/10 [00:00<00:00, 15.88it/s, Loss=0.294]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 52/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 52/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.295]
+Epoch 52/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.295]
+Epoch 52/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.288]
+Epoch 52/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.289]
+Epoch 52/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.3]  
+Epoch 52/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.292]
+Epoch 52/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.292]
+Epoch 52/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.291]
+Epoch 52/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.288]
+Epoch 52/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.291]
+Epoch 52/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.292]
+Epoch 52/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.67it/s, Loss=0.292]
+Epoch 52/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.67it/s, Loss=0.293]
+Epoch 52/10001: 100%|██████████| 10/10 [00:00<00:00, 13.15it/s, Loss=0.293]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 53/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 53/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.285]
+Epoch 53/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.285]
+Epoch 53/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.293]
+Epoch 53/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.297]
+Epoch 53/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.301]
+Epoch 53/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.29] 
+Epoch 53/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.292]
+Epoch 53/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.283]
+Epoch 53/10001:  70%|███████   | 7/10 [00:00<00:00, 19.66it/s, Loss=0.283]
+Epoch 53/10001:  70%|███████   | 7/10 [00:00<00:00, 19.66it/s, Loss=0.285]
+Epoch 53/10001:  70%|███████   | 7/10 [00:00<00:00, 19.66it/s, Loss=0.29] 
+Epoch 53/10001:  70%|███████   | 7/10 [00:00<00:00, 19.66it/s, Loss=0.289]
+Epoch 53/10001: 100%|██████████| 10/10 [00:00<00:00, 16.93it/s, Loss=0.289]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 54/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 54/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.288]
+Epoch 54/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.288]
+Epoch 54/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.293]
+Epoch 54/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.298]
+Epoch 54/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.295]
+Epoch 54/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.286]
+Epoch 54/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.292]
+Epoch 54/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.292]
+Epoch 54/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.288]
+Epoch 54/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.292]
+Epoch 54/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.296]
+Epoch 54/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.302]
+Epoch 54/10001: 100%|██████████| 10/10 [00:00<00:00, 15.40it/s, Loss=0.302]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 55/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 55/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.288]
+Epoch 55/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.288]
+Epoch 55/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.285]
+Epoch 55/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.295]
+Epoch 55/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.287]
+Epoch 55/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.293]
+Epoch 55/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.298]
+Epoch 55/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.298]
+Epoch 55/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.291]
+Epoch 55/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.292]
+Epoch 55/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.29] 
+Epoch 55/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.291]
+Epoch 55/10001: 100%|██████████| 10/10 [00:00<00:00, 14.01it/s, Loss=0.291]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 56/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 56/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.291]
+Epoch 56/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.291]
+Epoch 56/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.286]
+Epoch 56/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.288]
+Epoch 56/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.289]
+Epoch 56/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.291]
+Epoch 56/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.288]
+Epoch 56/10001:  60%|██████    | 6/10 [00:00<00:00, 15.92it/s, Loss=0.288]
+Epoch 56/10001:  60%|██████    | 6/10 [00:00<00:00, 15.92it/s, Loss=0.284]
+Epoch 56/10001:  60%|██████    | 6/10 [00:00<00:00, 15.92it/s, Loss=0.285]
+Epoch 56/10001:  60%|██████    | 6/10 [00:00<00:00, 15.92it/s, Loss=0.292]
+Epoch 56/10001:  60%|██████    | 6/10 [00:00<00:00, 15.92it/s, Loss=0.286]
+Epoch 56/10001: 100%|██████████| 10/10 [00:00<00:00, 14.31it/s, Loss=0.286]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 57/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 57/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.29]
+Epoch 57/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.29]
+Epoch 57/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.283]
+Epoch 57/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.283]
+Epoch 57/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.291]
+Epoch 57/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.292]
+Epoch 57/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.292]
+Epoch 57/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.282]
+Epoch 57/10001:  70%|███████   | 7/10 [00:00<00:00, 16.25it/s, Loss=0.282]
+Epoch 57/10001:  70%|███████   | 7/10 [00:00<00:00, 16.25it/s, Loss=0.293]
+Epoch 57/10001:  70%|███████   | 7/10 [00:00<00:00, 16.25it/s, Loss=0.292]
+Epoch 57/10001:  70%|███████   | 7/10 [00:00<00:00, 16.25it/s, Loss=0.29] 
+Epoch 57/10001: 100%|██████████| 10/10 [00:00<00:00, 14.13it/s, Loss=0.29]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 58/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 58/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.294]
+Epoch 58/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.294]
+Epoch 58/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.288]
+Epoch 58/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.289]
+Epoch 58/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.291]
+Epoch 58/10001:  40%|████      | 4/10 [00:00<00:00,  9.67it/s, Loss=0.291]
+Epoch 58/10001:  40%|████      | 4/10 [00:00<00:00,  9.67it/s, Loss=0.287]
+Epoch 58/10001:  40%|████      | 4/10 [00:00<00:00,  9.67it/s, Loss=0.288]
+Epoch 58/10001:  40%|████      | 4/10 [00:00<00:00,  9.67it/s, Loss=0.291]
+Epoch 58/10001:  40%|████      | 4/10 [00:00<00:00,  9.67it/s, Loss=0.289]
+Epoch 58/10001:  80%|████████  | 8/10 [00:00<00:00, 17.18it/s, Loss=0.289]
+Epoch 58/10001:  80%|████████  | 8/10 [00:00<00:00, 17.18it/s, Loss=0.287]
+Epoch 58/10001:  80%|████████  | 8/10 [00:00<00:00, 17.18it/s, Loss=0.282]
+Epoch 58/10001: 100%|██████████| 10/10 [00:00<00:00, 12.39it/s, Loss=0.282]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 59/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 59/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.286]
+Epoch 59/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.286]
+Epoch 59/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.286]
+Epoch 59/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.286]
+Epoch 59/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.292]
+Epoch 59/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.284]
+Epoch 59/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.293]
+Epoch 59/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.293]
+Epoch 59/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.292]
+Epoch 59/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.288]
+Epoch 59/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.286]
+Epoch 59/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.293]
+Epoch 59/10001: 100%|██████████| 10/10 [00:00<00:00, 15.48it/s, Loss=0.293]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 60/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 60/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.281]
+Epoch 60/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.281]
+Epoch 60/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.284]
+Epoch 60/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.278]
+Epoch 60/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.29] 
+Epoch 60/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.288]
+Epoch 60/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.28] 
+Epoch 60/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.289]
+Epoch 60/10001:  70%|███████   | 7/10 [00:00<00:00, 19.88it/s, Loss=0.289]
+Epoch 60/10001:  70%|███████   | 7/10 [00:00<00:00, 19.88it/s, Loss=0.29] 
+Epoch 60/10001:  70%|███████   | 7/10 [00:00<00:00, 19.88it/s, Loss=0.286]
+Epoch 60/10001:  70%|███████   | 7/10 [00:00<00:00, 19.88it/s, Loss=0.283]
+Epoch 60/10001: 100%|██████████| 10/10 [00:00<00:00, 16.95it/s, Loss=0.283]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 61/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 61/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.286]
+Epoch 61/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.286]
+Epoch 61/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.287]
+Epoch 61/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.286]
+Epoch 61/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.287]
+Epoch 61/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.284]
+Epoch 61/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.285]
+Epoch 61/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.291]
+Epoch 61/10001:  70%|███████   | 7/10 [00:00<00:00, 17.17it/s, Loss=0.291]
+Epoch 61/10001:  70%|███████   | 7/10 [00:00<00:00, 17.17it/s, Loss=0.286]
+Epoch 61/10001:  70%|███████   | 7/10 [00:00<00:00, 17.17it/s, Loss=0.279]
+Epoch 61/10001:  70%|███████   | 7/10 [00:00<00:00, 17.17it/s, Loss=0.275]
+Epoch 61/10001: 100%|██████████| 10/10 [00:00<00:00, 14.42it/s, Loss=0.275]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 62/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 62/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.287]
+Epoch 62/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.287]
+Epoch 62/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.287]
+Epoch 62/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.288]
+Epoch 62/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.291]
+Epoch 62/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.288]
+Epoch 62/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.289]
+Epoch 62/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.292]
+Epoch 62/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.285]
+Epoch 62/10001:  80%|████████  | 8/10 [00:00<00:00, 18.17it/s, Loss=0.285]
+Epoch 62/10001:  80%|████████  | 8/10 [00:00<00:00, 18.17it/s, Loss=0.286]
+Epoch 62/10001:  80%|████████  | 8/10 [00:00<00:00, 18.17it/s, Loss=0.291]
+Epoch 62/10001: 100%|██████████| 10/10 [00:00<00:00, 14.17it/s, Loss=0.291]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 63/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 63/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.297]
+Epoch 63/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.297]
+Epoch 63/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.296]
+Epoch 63/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.286]
+Epoch 63/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.287]
+Epoch 63/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.286]
+Epoch 63/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.286]
+Epoch 63/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.29] 
+Epoch 63/10001:  70%|███████   | 7/10 [00:00<00:00, 16.11it/s, Loss=0.29]
+Epoch 63/10001:  70%|███████   | 7/10 [00:00<00:00, 16.11it/s, Loss=0.293]
+Epoch 63/10001:  70%|███████   | 7/10 [00:00<00:00, 16.11it/s, Loss=0.287]
+Epoch 63/10001:  70%|███████   | 7/10 [00:00<00:00, 16.11it/s, Loss=0.289]
+Epoch 63/10001: 100%|██████████| 10/10 [00:00<00:00, 14.37it/s, Loss=0.289]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 64/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 64/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.287]
+Epoch 64/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.287]
+Epoch 64/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.288]
+Epoch 64/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.288]
+Epoch 64/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.281]
+Epoch 64/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.286]
+Epoch 64/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.29] 
+Epoch 64/10001:  60%|██████    | 6/10 [00:00<00:00, 16.56it/s, Loss=0.29]
+Epoch 64/10001:  60%|██████    | 6/10 [00:00<00:00, 16.56it/s, Loss=0.291]
+Epoch 64/10001:  60%|██████    | 6/10 [00:00<00:00, 16.56it/s, Loss=0.288]
+Epoch 64/10001:  60%|██████    | 6/10 [00:00<00:00, 16.56it/s, Loss=0.279]
+Epoch 64/10001:  60%|██████    | 6/10 [00:00<00:00, 16.56it/s, Loss=0.284]
+Epoch 64/10001: 100%|██████████| 10/10 [00:00<00:00, 15.39it/s, Loss=0.284]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 65/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 65/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.282]
+Epoch 65/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.282]
+Epoch 65/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.287]
+Epoch 65/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.281]
+Epoch 65/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.29] 
+Epoch 65/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.287]
+Epoch 65/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.284]
+Epoch 65/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.284]
+Epoch 65/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.283]
+Epoch 65/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.289]
+Epoch 65/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.285]
+Epoch 65/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.291]
+Epoch 65/10001: 100%|██████████| 10/10 [00:00<00:00, 13.15it/s, Loss=0.291]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 66/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 66/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.284]
+Epoch 66/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.284]
+Epoch 66/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.283]
+Epoch 66/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.286]
+Epoch 66/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.287]
+Epoch 66/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.286]
+Epoch 66/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.282]
+Epoch 66/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.282]
+Epoch 66/10001:  70%|███████   | 7/10 [00:00<00:00, 15.37it/s, Loss=0.282]
+Epoch 66/10001:  70%|███████   | 7/10 [00:00<00:00, 15.37it/s, Loss=0.281]
+Epoch 66/10001:  70%|███████   | 7/10 [00:00<00:00, 15.37it/s, Loss=0.29] 
+Epoch 66/10001:  70%|███████   | 7/10 [00:00<00:00, 15.37it/s, Loss=0.281]
+Epoch 66/10001: 100%|██████████| 10/10 [00:00<00:00, 13.36it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 67/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 67/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.29]
+Epoch 67/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.29]
+Epoch 67/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.287]
+Epoch 67/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.276]
+Epoch 67/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.287]
+Epoch 67/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.292]
+Epoch 67/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.288]
+Epoch 67/10001:  60%|██████    | 6/10 [00:00<00:00, 14.79it/s, Loss=0.288]
+Epoch 67/10001:  60%|██████    | 6/10 [00:00<00:00, 14.79it/s, Loss=0.283]
+Epoch 67/10001:  60%|██████    | 6/10 [00:00<00:00, 14.79it/s, Loss=0.282]
+Epoch 67/10001:  60%|██████    | 6/10 [00:00<00:00, 14.79it/s, Loss=0.289]
+Epoch 67/10001:  60%|██████    | 6/10 [00:00<00:00, 14.79it/s, Loss=0.288]
+Epoch 67/10001: 100%|██████████| 10/10 [00:00<00:00, 14.30it/s, Loss=0.288]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 68/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 68/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.279]
+Epoch 68/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.279]
+Epoch 68/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.294]
+Epoch 68/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.29] 
+Epoch 68/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.279]
+Epoch 68/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.283]
+Epoch 68/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.289]
+Epoch 68/10001:  60%|██████    | 6/10 [00:00<00:00, 15.21it/s, Loss=0.289]
+Epoch 68/10001:  60%|██████    | 6/10 [00:00<00:00, 15.21it/s, Loss=0.287]
+Epoch 68/10001:  60%|██████    | 6/10 [00:00<00:00, 15.21it/s, Loss=0.285]
+Epoch 68/10001:  60%|██████    | 6/10 [00:00<00:00, 15.21it/s, Loss=0.283]
+Epoch 68/10001:  60%|██████    | 6/10 [00:00<00:00, 15.21it/s, Loss=0.281]
+Epoch 68/10001: 100%|██████████| 10/10 [00:00<00:00, 14.98it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 69/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 69/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.28]
+Epoch 69/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.28]
+Epoch 69/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.29]
+Epoch 69/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.284]
+Epoch 69/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.283]
+Epoch 69/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.284]
+Epoch 69/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.29] 
+Epoch 69/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.285]
+Epoch 69/10001:  70%|███████   | 7/10 [00:00<00:00, 19.06it/s, Loss=0.285]
+Epoch 69/10001:  70%|███████   | 7/10 [00:00<00:00, 19.06it/s, Loss=0.287]
+Epoch 69/10001:  70%|███████   | 7/10 [00:00<00:00, 19.06it/s, Loss=0.288]
+Epoch 69/10001:  70%|███████   | 7/10 [00:00<00:00, 19.06it/s, Loss=0.289]
+Epoch 69/10001: 100%|██████████| 10/10 [00:00<00:00, 16.07it/s, Loss=0.289]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 70/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 70/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.286]
+Epoch 70/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.286]
+Epoch 70/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.282]
+Epoch 70/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.29] 
+Epoch 70/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.291]
+Epoch 70/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.286]
+Epoch 70/10001:  50%|█████     | 5/10 [00:00<00:00, 13.03it/s, Loss=0.286]
+Epoch 70/10001:  50%|█████     | 5/10 [00:00<00:00, 13.03it/s, Loss=0.291]
+Epoch 70/10001:  50%|█████     | 5/10 [00:00<00:00, 13.03it/s, Loss=0.285]
+Epoch 70/10001:  50%|█████     | 5/10 [00:00<00:00, 13.03it/s, Loss=0.286]
+Epoch 70/10001:  50%|█████     | 5/10 [00:00<00:00, 13.03it/s, Loss=0.285]
+Epoch 70/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.94it/s, Loss=0.285]
+Epoch 70/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.94it/s, Loss=0.281]
+Epoch 70/10001: 100%|██████████| 10/10 [00:00<00:00, 14.04it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 71/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 71/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.289]
+Epoch 71/10001:  10%|█         | 1/10 [00:00<00:02,  3.07it/s, Loss=0.289]
+Epoch 71/10001:  10%|█         | 1/10 [00:00<00:02,  3.07it/s, Loss=0.28] 
+Epoch 71/10001:  10%|█         | 1/10 [00:00<00:02,  3.07it/s, Loss=0.286]
+Epoch 71/10001:  10%|█         | 1/10 [00:00<00:02,  3.07it/s, Loss=0.283]
+Epoch 71/10001:  10%|█         | 1/10 [00:00<00:02,  3.07it/s, Loss=0.282]
+Epoch 71/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.282]
+Epoch 71/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.283]
+Epoch 71/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.282]
+Epoch 71/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.286]
+Epoch 71/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.28] 
+Epoch 71/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.11it/s, Loss=0.28]
+Epoch 71/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.11it/s, Loss=0.285]
+Epoch 71/10001: 100%|██████████| 10/10 [00:00<00:00, 14.18it/s, Loss=0.285]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 72/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 72/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.28]
+Epoch 72/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.28]
+Epoch 72/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.279]
+Epoch 72/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.281]
+Epoch 72/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.286]
+Epoch 72/10001:  40%|████      | 4/10 [00:00<00:00,  9.02it/s, Loss=0.286]
+Epoch 72/10001:  40%|████      | 4/10 [00:00<00:00,  9.02it/s, Loss=0.284]
+Epoch 72/10001:  40%|████      | 4/10 [00:00<00:00,  9.02it/s, Loss=0.277]
+Epoch 72/10001:  40%|████      | 4/10 [00:00<00:00,  9.02it/s, Loss=0.282]
+Epoch 72/10001:  40%|████      | 4/10 [00:00<00:00,  9.02it/s, Loss=0.29] 
+Epoch 72/10001:  80%|████████  | 8/10 [00:00<00:00, 16.66it/s, Loss=0.29]
+Epoch 72/10001:  80%|████████  | 8/10 [00:00<00:00, 16.66it/s, Loss=0.275]
+Epoch 72/10001:  80%|████████  | 8/10 [00:00<00:00, 16.66it/s, Loss=0.277]
+Epoch 72/10001: 100%|██████████| 10/10 [00:00<00:00, 12.57it/s, Loss=0.277]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 73/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 73/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.283]
+Epoch 73/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.283]
+Epoch 73/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.282]
+Epoch 73/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.285]
+Epoch 73/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.285]
+Epoch 73/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.283]
+Epoch 73/10001:  10%|█         | 1/10 [00:00<00:03,  2.56it/s, Loss=0.281]
+Epoch 73/10001:  60%|██████    | 6/10 [00:00<00:00, 14.82it/s, Loss=0.281]
+Epoch 73/10001:  60%|██████    | 6/10 [00:00<00:00, 14.82it/s, Loss=0.288]
+Epoch 73/10001:  60%|██████    | 6/10 [00:00<00:00, 14.82it/s, Loss=0.286]
+Epoch 73/10001:  60%|██████    | 6/10 [00:00<00:00, 14.82it/s, Loss=0.288]
+Epoch 73/10001:  60%|██████    | 6/10 [00:00<00:00, 14.82it/s, Loss=0.291]
+Epoch 73/10001: 100%|██████████| 10/10 [00:00<00:00, 14.74it/s, Loss=0.291]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 74/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 74/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.286]
+Epoch 74/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.286]
+Epoch 74/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.278]
+Epoch 74/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.283]
+Epoch 74/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.28] 
+Epoch 74/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.286]
+Epoch 74/10001:  50%|█████     | 5/10 [00:00<00:00, 13.94it/s, Loss=0.286]
+Epoch 74/10001:  50%|█████     | 5/10 [00:00<00:00, 13.94it/s, Loss=0.29] 
+Epoch 74/10001:  50%|█████     | 5/10 [00:00<00:00, 13.94it/s, Loss=0.285]
+Epoch 74/10001:  50%|█████     | 5/10 [00:00<00:00, 13.94it/s, Loss=0.286]
+Epoch 74/10001:  50%|█████     | 5/10 [00:00<00:00, 13.94it/s, Loss=0.285]
+Epoch 74/10001:  50%|█████     | 5/10 [00:00<00:00, 13.94it/s, Loss=0.284]
+Epoch 74/10001: 100%|██████████| 10/10 [00:00<00:00, 15.37it/s, Loss=0.284]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 75/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 75/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.284]
+Epoch 75/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.284]
+Epoch 75/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.285]
+Epoch 75/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.288]
+Epoch 75/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.28] 
+Epoch 75/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.288]
+Epoch 75/10001:  50%|█████     | 5/10 [00:00<00:00, 10.28it/s, Loss=0.288]
+Epoch 75/10001:  50%|█████     | 5/10 [00:00<00:00, 10.28it/s, Loss=0.28] 
+Epoch 75/10001:  50%|█████     | 5/10 [00:00<00:00, 10.28it/s, Loss=0.276]
+Epoch 75/10001:  50%|█████     | 5/10 [00:00<00:00, 10.28it/s, Loss=0.28] 
+Epoch 75/10001:  50%|█████     | 5/10 [00:00<00:00, 10.28it/s, Loss=0.281]
+Epoch 75/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.04it/s, Loss=0.281]
+Epoch 75/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.04it/s, Loss=0.28] 
+Epoch 75/10001: 100%|██████████| 10/10 [00:00<00:00, 11.68it/s, Loss=0.28]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 76/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 76/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.282]
+Epoch 76/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.282]
+Epoch 76/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.279]
+Epoch 76/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.281]
+Epoch 76/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.274]
+Epoch 76/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.281]
+Epoch 76/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.279]
+Epoch 76/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.279]
+Epoch 76/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.282]
+Epoch 76/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.279]
+Epoch 76/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.282]
+Epoch 76/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.287]
+Epoch 76/10001: 100%|██████████| 10/10 [00:00<00:00, 13.19it/s, Loss=0.287]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 77/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 77/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.281]
+Epoch 77/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.281]
+Epoch 77/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.281]
+Epoch 77/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.277]
+Epoch 77/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.281]
+Epoch 77/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.28] 
+Epoch 77/10001:  50%|█████     | 5/10 [00:00<00:00, 10.83it/s, Loss=0.28]
+Epoch 77/10001:  50%|█████     | 5/10 [00:00<00:00, 10.83it/s, Loss=0.278]
+Epoch 77/10001:  50%|█████     | 5/10 [00:00<00:00, 10.83it/s, Loss=0.28] 
+Epoch 77/10001:  50%|█████     | 5/10 [00:00<00:00, 10.83it/s, Loss=0.285]
+Epoch 77/10001:  50%|█████     | 5/10 [00:00<00:00, 10.83it/s, Loss=0.279]
+Epoch 77/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.41it/s, Loss=0.279]
+Epoch 77/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.41it/s, Loss=0.281]
+Epoch 77/10001: 100%|██████████| 10/10 [00:00<00:00, 12.18it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 78/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 78/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.293]
+Epoch 78/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.293]
+Epoch 78/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.285]
+Epoch 78/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.282]
+Epoch 78/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.28] 
+Epoch 78/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.278]
+Epoch 78/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.278]
+Epoch 78/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.281]
+Epoch 78/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.285]
+Epoch 78/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.287]
+Epoch 78/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.28] 
+Epoch 78/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.277]
+Epoch 78/10001: 100%|██████████| 10/10 [00:00<00:00, 19.19it/s, Loss=0.277]
+Epoch 78/10001: 100%|██████████| 10/10 [00:00<00:00, 12.26it/s, Loss=0.277]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 79/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 79/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.283]
+Epoch 79/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.283]
+Epoch 79/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.283]
+Epoch 79/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.285]
+Epoch 79/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.28] 
+Epoch 79/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.283]
+Epoch 79/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.283]
+Epoch 79/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.278]
+Epoch 79/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.279]
+Epoch 79/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.278]
+Epoch 79/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.275]
+Epoch 79/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.35it/s, Loss=0.275]
+Epoch 79/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.35it/s, Loss=0.282]
+Epoch 79/10001: 100%|██████████| 10/10 [00:00<00:00, 12.98it/s, Loss=0.282]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 80/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 80/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.283]
+Epoch 80/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.283]
+Epoch 80/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.284]
+Epoch 80/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.284]
+Epoch 80/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.283]
+Epoch 80/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.278]
+Epoch 80/10001:  50%|█████     | 5/10 [00:00<00:00, 11.96it/s, Loss=0.278]
+Epoch 80/10001:  50%|█████     | 5/10 [00:00<00:00, 11.96it/s, Loss=0.271]
+Epoch 80/10001:  50%|█████     | 5/10 [00:00<00:00, 11.96it/s, Loss=0.275]
+Epoch 80/10001:  50%|█████     | 5/10 [00:00<00:00, 11.96it/s, Loss=0.28] 
+Epoch 80/10001:  50%|█████     | 5/10 [00:00<00:00, 11.96it/s, Loss=0.277]
+Epoch 80/10001:  50%|█████     | 5/10 [00:00<00:00, 11.96it/s, Loss=0.281]
+Epoch 80/10001: 100%|██████████| 10/10 [00:00<00:00, 13.86it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 81/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 81/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.287]
+Epoch 81/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.287]
+Epoch 81/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.277]
+Epoch 81/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.281]
+Epoch 81/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.282]
+Epoch 81/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.283]
+Epoch 81/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.29] 
+Epoch 81/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.276]
+Epoch 81/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.275]
+Epoch 81/10001:  80%|████████  | 8/10 [00:00<00:00, 18.41it/s, Loss=0.275]
+Epoch 81/10001:  80%|████████  | 8/10 [00:00<00:00, 18.41it/s, Loss=0.282]
+Epoch 81/10001:  80%|████████  | 8/10 [00:00<00:00, 18.41it/s, Loss=0.27] 
+Epoch 81/10001: 100%|██████████| 10/10 [00:00<00:00, 14.62it/s, Loss=0.27]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 82/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 82/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.288]
+Epoch 82/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.288]
+Epoch 82/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.286]
+Epoch 82/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.282]
+Epoch 82/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.287]
+Epoch 82/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.287]
+Epoch 82/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.281]
+Epoch 82/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.282]
+Epoch 82/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.281]
+Epoch 82/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.279]
+Epoch 82/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.284]
+Epoch 82/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.18it/s, Loss=0.284]
+Epoch 82/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.18it/s, Loss=0.286]
+Epoch 82/10001: 100%|██████████| 10/10 [00:00<00:00, 13.49it/s, Loss=0.286]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 83/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 83/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.282]
+Epoch 83/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.282]
+Epoch 83/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.278]
+Epoch 83/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.281]
+Epoch 83/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.281]
+Epoch 83/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.283]
+Epoch 83/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.283]
+Epoch 83/10001:  60%|██████    | 6/10 [00:00<00:00, 13.22it/s, Loss=0.283]
+Epoch 83/10001:  60%|██████    | 6/10 [00:00<00:00, 13.22it/s, Loss=0.277]
+Epoch 83/10001:  60%|██████    | 6/10 [00:00<00:00, 13.22it/s, Loss=0.276]
+Epoch 83/10001:  60%|██████    | 6/10 [00:00<00:00, 13.22it/s, Loss=0.283]
+Epoch 83/10001:  60%|██████    | 6/10 [00:00<00:00, 13.22it/s, Loss=0.28] 
+Epoch 83/10001: 100%|██████████| 10/10 [00:00<00:00, 13.12it/s, Loss=0.28]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 84/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 84/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.287]
+Epoch 84/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.287]
+Epoch 84/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.278]
+Epoch 84/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.283]
+Epoch 84/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.288]
+Epoch 84/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.279]
+Epoch 84/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.283]
+Epoch 84/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.285]
+Epoch 84/10001:  70%|███████   | 7/10 [00:00<00:00, 19.52it/s, Loss=0.285]
+Epoch 84/10001:  70%|███████   | 7/10 [00:00<00:00, 19.52it/s, Loss=0.284]
+Epoch 84/10001:  70%|███████   | 7/10 [00:00<00:00, 19.52it/s, Loss=0.279]
+Epoch 84/10001:  70%|███████   | 7/10 [00:00<00:00, 19.52it/s, Loss=0.284]
+Epoch 84/10001: 100%|██████████| 10/10 [00:00<00:00, 16.65it/s, Loss=0.284]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 85/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 85/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.282]
+Epoch 85/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.282]
+Epoch 85/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.279]
+Epoch 85/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.279]
+Epoch 85/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.281]
+Epoch 85/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.284]
+Epoch 85/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.284]
+Epoch 85/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.277]
+Epoch 85/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.279]
+Epoch 85/10001:  80%|████████  | 8/10 [00:00<00:00, 21.06it/s, Loss=0.279]
+Epoch 85/10001:  80%|████████  | 8/10 [00:00<00:00, 21.06it/s, Loss=0.273]
+Epoch 85/10001:  80%|████████  | 8/10 [00:00<00:00, 21.06it/s, Loss=0.28] 
+Epoch 85/10001: 100%|██████████| 10/10 [00:00<00:00, 16.30it/s, Loss=0.28]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 86/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 86/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.277]
+Epoch 86/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.277]
+Epoch 86/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.275]
+Epoch 86/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.272]
+Epoch 86/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.27] 
+Epoch 86/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.275]
+Epoch 86/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.275]
+Epoch 86/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.28] 
+Epoch 86/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.279]
+Epoch 86/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.275]
+Epoch 86/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.277]
+Epoch 86/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.281]
+Epoch 86/10001: 100%|██████████| 10/10 [00:00<00:00, 21.37it/s, Loss=0.281]
+Epoch 86/10001: 100%|██████████| 10/10 [00:00<00:00, 13.44it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 87/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 87/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.279]
+Epoch 87/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.279]
+Epoch 87/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.281]
+Epoch 87/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.277]
+Epoch 87/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.285]
+Epoch 87/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.269]
+Epoch 87/10001:  50%|█████     | 5/10 [00:00<00:00, 11.41it/s, Loss=0.269]
+Epoch 87/10001:  50%|█████     | 5/10 [00:00<00:00, 11.41it/s, Loss=0.283]
+Epoch 87/10001:  50%|█████     | 5/10 [00:00<00:00, 11.41it/s, Loss=0.274]
+Epoch 87/10001:  50%|█████     | 5/10 [00:00<00:00, 11.41it/s, Loss=0.28] 
+Epoch 87/10001:  50%|█████     | 5/10 [00:00<00:00, 11.41it/s, Loss=0.281]
+Epoch 87/10001:  50%|█████     | 5/10 [00:00<00:00, 11.41it/s, Loss=0.276]
+Epoch 87/10001: 100%|██████████| 10/10 [00:00<00:00, 13.42it/s, Loss=0.276]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 88/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 88/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.283]
+Epoch 88/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.283]
+Epoch 88/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.28] 
+Epoch 88/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.282]
+Epoch 88/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.284]
+Epoch 88/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.285]
+Epoch 88/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.285]
+Epoch 88/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.285]
+Epoch 88/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.278]
+Epoch 88/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.279]
+Epoch 88/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.284]
+Epoch 88/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.275]
+Epoch 88/10001: 100%|██████████| 10/10 [00:00<00:00, 14.63it/s, Loss=0.275]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 89/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 89/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.28]
+Epoch 89/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.28]
+Epoch 89/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.28]
+Epoch 89/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.275]
+Epoch 89/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.279]
+Epoch 89/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.281]
+Epoch 89/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.281]
+Epoch 89/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.276]
+Epoch 89/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.281]
+Epoch 89/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.282]
+Epoch 89/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.283]
+Epoch 89/10001:  50%|█████     | 5/10 [00:00<00:00, 12.17it/s, Loss=0.281]
+Epoch 89/10001: 100%|██████████| 10/10 [00:00<00:00, 22.11it/s, Loss=0.281]
+Epoch 89/10001: 100%|██████████| 10/10 [00:00<00:00, 13.35it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 90/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 90/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.276]
+Epoch 90/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.276]
+Epoch 90/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.275]
+Epoch 90/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.285]
+Epoch 90/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.289]
+Epoch 90/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.274]
+Epoch 90/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.273]
+Epoch 90/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.277]
+Epoch 90/10001:  70%|███████   | 7/10 [00:00<00:00, 16.31it/s, Loss=0.277]
+Epoch 90/10001:  70%|███████   | 7/10 [00:00<00:00, 16.31it/s, Loss=0.279]
+Epoch 90/10001:  70%|███████   | 7/10 [00:00<00:00, 16.31it/s, Loss=0.278]
+Epoch 90/10001:  70%|███████   | 7/10 [00:00<00:00, 16.31it/s, Loss=0.277]
+Epoch 90/10001: 100%|██████████| 10/10 [00:00<00:00, 14.01it/s, Loss=0.277]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 91/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 91/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.285]
+Epoch 91/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.285]
+Epoch 91/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.28] 
+Epoch 91/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.271]
+Epoch 91/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.277]
+Epoch 91/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.28] 
+Epoch 91/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.273]
+Epoch 91/10001:  60%|██████    | 6/10 [00:00<00:00, 16.45it/s, Loss=0.273]
+Epoch 91/10001:  60%|██████    | 6/10 [00:00<00:00, 16.45it/s, Loss=0.281]
+Epoch 91/10001:  60%|██████    | 6/10 [00:00<00:00, 16.45it/s, Loss=0.277]
+Epoch 91/10001:  60%|██████    | 6/10 [00:00<00:00, 16.45it/s, Loss=0.278]
+Epoch 91/10001:  60%|██████    | 6/10 [00:00<00:00, 16.45it/s, Loss=0.281]
+Epoch 91/10001: 100%|██████████| 10/10 [00:00<00:00, 16.20it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 92/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 92/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.279]
+Epoch 92/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.279]
+Epoch 92/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.273]
+Epoch 92/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.276]
+Epoch 92/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.28] 
+Epoch 92/10001:  40%|████      | 4/10 [00:00<00:00, 10.71it/s, Loss=0.28]
+Epoch 92/10001:  40%|████      | 4/10 [00:00<00:00, 10.71it/s, Loss=0.284]
+Epoch 92/10001:  40%|████      | 4/10 [00:00<00:00, 10.71it/s, Loss=0.278]
+Epoch 92/10001:  40%|████      | 4/10 [00:00<00:00, 10.71it/s, Loss=0.276]
+Epoch 92/10001:  40%|████      | 4/10 [00:00<00:00, 10.71it/s, Loss=0.276]
+Epoch 92/10001:  80%|████████  | 8/10 [00:00<00:00, 18.65it/s, Loss=0.276]
+Epoch 92/10001:  80%|████████  | 8/10 [00:00<00:00, 18.65it/s, Loss=0.274]
+Epoch 92/10001:  80%|████████  | 8/10 [00:00<00:00, 18.65it/s, Loss=0.276]
+Epoch 92/10001: 100%|██████████| 10/10 [00:00<00:00, 13.20it/s, Loss=0.276]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 93/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 93/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.279]
+Epoch 93/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.279]
+Epoch 93/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.271]
+Epoch 93/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.282]
+Epoch 93/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.277]
+Epoch 93/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.279]
+Epoch 93/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.279]
+Epoch 93/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.271]
+Epoch 93/10001:  70%|███████   | 7/10 [00:00<00:00, 18.07it/s, Loss=0.271]
+Epoch 93/10001:  70%|███████   | 7/10 [00:00<00:00, 18.07it/s, Loss=0.28] 
+Epoch 93/10001:  70%|███████   | 7/10 [00:00<00:00, 18.07it/s, Loss=0.276]
+Epoch 93/10001:  70%|███████   | 7/10 [00:00<00:00, 18.07it/s, Loss=0.277]
+Epoch 93/10001: 100%|██████████| 10/10 [00:00<00:00, 14.95it/s, Loss=0.277]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 94/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 94/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.279]
+Epoch 94/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.279]
+Epoch 94/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.28] 
+Epoch 94/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.273]
+Epoch 94/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.272]
+Epoch 94/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.279]
+Epoch 94/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.283]
+Epoch 94/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.283]
+Epoch 94/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.277]
+Epoch 94/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.276]
+Epoch 94/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.276]
+Epoch 94/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.281]
+Epoch 94/10001: 100%|██████████| 10/10 [00:00<00:00, 13.39it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 95/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 95/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.275]
+Epoch 95/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.275]
+Epoch 95/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.275]
+Epoch 95/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.281]
+Epoch 95/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.27] 
+Epoch 95/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.272]
+Epoch 95/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.272]
+Epoch 95/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.273]
+Epoch 95/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.274]
+Epoch 95/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.28] 
+Epoch 95/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.278]
+Epoch 95/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.63it/s, Loss=0.278]
+Epoch 95/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.63it/s, Loss=0.275]
+Epoch 95/10001: 100%|██████████| 10/10 [00:00<00:00, 13.16it/s, Loss=0.275]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 96/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 96/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.274]
+Epoch 96/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.274]
+Epoch 96/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.278]
+Epoch 96/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.285]
+Epoch 96/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.274]
+Epoch 96/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.276]
+Epoch 96/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.283]
+Epoch 96/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.276]
+Epoch 96/10001:  70%|███████   | 7/10 [00:00<00:00, 16.33it/s, Loss=0.276]
+Epoch 96/10001:  70%|███████   | 7/10 [00:00<00:00, 16.33it/s, Loss=0.28] 
+Epoch 96/10001:  70%|███████   | 7/10 [00:00<00:00, 16.33it/s, Loss=0.284]
+Epoch 96/10001:  70%|███████   | 7/10 [00:00<00:00, 16.33it/s, Loss=0.284]
+Epoch 96/10001: 100%|██████████| 10/10 [00:00<00:00, 14.16it/s, Loss=0.284]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 97/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 97/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.275]
+Epoch 97/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.275]
+Epoch 97/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.277]
+Epoch 97/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.272]
+Epoch 97/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.275]
+Epoch 97/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.275]
+Epoch 97/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.283]
+Epoch 97/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.277]
+Epoch 97/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.277]
+Epoch 97/10001:  80%|████████  | 8/10 [00:00<00:00, 21.79it/s, Loss=0.277]
+Epoch 97/10001:  80%|████████  | 8/10 [00:00<00:00, 21.79it/s, Loss=0.277]
+Epoch 97/10001:  80%|████████  | 8/10 [00:00<00:00, 21.79it/s, Loss=0.273]
+Epoch 97/10001: 100%|██████████| 10/10 [00:00<00:00, 16.54it/s, Loss=0.273]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 98/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 98/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.278]
+Epoch 98/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.278]
+Epoch 98/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.289]
+Epoch 98/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.28] 
+Epoch 98/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.276]
+Epoch 98/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.273]
+Epoch 98/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.277]
+Epoch 98/10001:  60%|██████    | 6/10 [00:00<00:00, 13.87it/s, Loss=0.277]
+Epoch 98/10001:  60%|██████    | 6/10 [00:00<00:00, 13.87it/s, Loss=0.275]
+Epoch 98/10001:  60%|██████    | 6/10 [00:00<00:00, 13.87it/s, Loss=0.277]
+Epoch 98/10001:  60%|██████    | 6/10 [00:00<00:00, 13.87it/s, Loss=0.281]
+Epoch 98/10001:  60%|██████    | 6/10 [00:00<00:00, 13.87it/s, Loss=0.274]
+Epoch 98/10001: 100%|██████████| 10/10 [00:00<00:00, 20.40it/s, Loss=0.274]
+Epoch 98/10001: 100%|██████████| 10/10 [00:00<00:00, 13.18it/s, Loss=0.274]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 99/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 99/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.274]
+Epoch 99/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.274]
+Epoch 99/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.283]
+Epoch 99/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.276]
+Epoch 99/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.271]
+Epoch 99/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.279]
+Epoch 99/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.276]
+Epoch 99/10001:  60%|██████    | 6/10 [00:00<00:00, 16.93it/s, Loss=0.276]
+Epoch 99/10001:  60%|██████    | 6/10 [00:00<00:00, 16.93it/s, Loss=0.279]
+Epoch 99/10001:  60%|██████    | 6/10 [00:00<00:00, 16.93it/s, Loss=0.271]
+Epoch 99/10001:  60%|██████    | 6/10 [00:00<00:00, 16.93it/s, Loss=0.28] 
+Epoch 99/10001:  60%|██████    | 6/10 [00:00<00:00, 16.93it/s, Loss=0.278]
+Epoch 99/10001: 100%|██████████| 10/10 [00:00<00:00, 15.88it/s, Loss=0.278]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 100/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 100/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.279]
+Epoch 100/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.279]
+Epoch 100/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.273]
+Epoch 100/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.271]
+Epoch 100/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.269]
+Epoch 100/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.271]
+Epoch 100/10001:  50%|█████     | 5/10 [00:00<00:00, 12.72it/s, Loss=0.271]
+Epoch 100/10001:  50%|█████     | 5/10 [00:00<00:00, 12.72it/s, Loss=0.275]
+Epoch 100/10001:  50%|█████     | 5/10 [00:00<00:00, 12.72it/s, Loss=0.276]
+Epoch 100/10001:  50%|█████     | 5/10 [00:00<00:00, 12.72it/s, Loss=0.279]
+Epoch 100/10001:  50%|█████     | 5/10 [00:00<00:00, 12.72it/s, Loss=0.274]
+Epoch 100/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.24it/s, Loss=0.274]
+Epoch 100/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.24it/s, Loss=0.27] 
+Epoch 100/10001: 100%|██████████| 10/10 [00:00<00:00, 13.99it/s, Loss=0.27]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 101/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 101/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.271]
+Epoch 101/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.271]
+Epoch 101/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.275]
+Epoch 101/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.272]
+Epoch 101/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.274]
+Epoch 101/10001:  40%|████      | 4/10 [00:00<00:00,  8.91it/s, Loss=0.274]
+Epoch 101/10001:  40%|████      | 4/10 [00:00<00:00,  8.91it/s, Loss=0.277]
+Epoch 101/10001:  40%|████      | 4/10 [00:00<00:00,  8.91it/s, Loss=0.285]
+Epoch 101/10001:  40%|████      | 4/10 [00:00<00:00,  8.91it/s, Loss=0.27] 
+Epoch 101/10001:  40%|████      | 4/10 [00:00<00:00,  8.91it/s, Loss=0.273]
+Epoch 101/10001:  80%|████████  | 8/10 [00:00<00:00, 16.42it/s, Loss=0.273]
+Epoch 101/10001:  80%|████████  | 8/10 [00:00<00:00, 16.42it/s, Loss=0.278]
+Epoch 101/10001:  80%|████████  | 8/10 [00:00<00:00, 16.42it/s, Loss=0.271]
+Epoch 101/10001: 100%|██████████| 10/10 [00:00<00:00, 12.23it/s, Loss=0.271]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 102/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 102/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.277]
+Epoch 102/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.277]
+Epoch 102/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.28] 
+Epoch 102/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.273]
+Epoch 102/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.281]
+Epoch 102/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.273]
+Epoch 102/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.279]
+Epoch 102/10001:  60%|██████    | 6/10 [00:00<00:00, 16.37it/s, Loss=0.279]
+Epoch 102/10001:  60%|██████    | 6/10 [00:00<00:00, 16.37it/s, Loss=0.273]
+Epoch 102/10001:  60%|██████    | 6/10 [00:00<00:00, 16.37it/s, Loss=0.28] 
+Epoch 102/10001:  60%|██████    | 6/10 [00:00<00:00, 16.37it/s, Loss=0.277]
+Epoch 102/10001:  60%|██████    | 6/10 [00:00<00:00, 16.37it/s, Loss=0.284]
+Epoch 102/10001: 100%|██████████| 10/10 [00:00<00:00, 15.54it/s, Loss=0.284]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 103/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 103/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.278]
+Epoch 103/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.278]
+Epoch 103/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.269]
+Epoch 103/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.273]
+Epoch 103/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.278]
+Epoch 103/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.274]
+Epoch 103/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.28] 
+Epoch 103/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.28]
+Epoch 103/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.28]
+Epoch 103/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.275]
+Epoch 103/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.275]
+Epoch 103/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.281]
+Epoch 103/10001: 100%|██████████| 10/10 [00:00<00:00, 15.22it/s, Loss=0.281]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 104/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 104/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.273]
+Epoch 104/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.273]
+Epoch 104/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.275]
+Epoch 104/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.281]
+Epoch 104/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.279]
+Epoch 104/10001:  40%|████      | 4/10 [00:00<00:00, 10.07it/s, Loss=0.279]
+Epoch 104/10001:  40%|████      | 4/10 [00:00<00:00, 10.07it/s, Loss=0.27] 
+Epoch 104/10001:  40%|████      | 4/10 [00:00<00:00, 10.07it/s, Loss=0.283]
+Epoch 104/10001:  40%|████      | 4/10 [00:00<00:00, 10.07it/s, Loss=0.273]
+Epoch 104/10001:  40%|████      | 4/10 [00:00<00:00, 10.07it/s, Loss=0.27] 
+Epoch 104/10001:  40%|████      | 4/10 [00:00<00:00, 10.07it/s, Loss=0.272]
+Epoch 104/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.98it/s, Loss=0.272]
+Epoch 104/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.98it/s, Loss=0.271]
+Epoch 104/10001: 100%|██████████| 10/10 [00:00<00:00, 13.70it/s, Loss=0.271]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 105/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 105/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.272]
+Epoch 105/10001:  10%|█         | 1/10 [00:00<00:04,  2.00it/s, Loss=0.272]
+Epoch 105/10001:  10%|█         | 1/10 [00:00<00:04,  2.00it/s, Loss=0.274]
+Epoch 105/10001:  10%|█         | 1/10 [00:00<00:04,  2.00it/s, Loss=0.281]
+Epoch 105/10001:  10%|█         | 1/10 [00:00<00:04,  2.00it/s, Loss=0.278]
+Epoch 105/10001:  10%|█         | 1/10 [00:00<00:04,  2.00it/s, Loss=0.278]
+Epoch 105/10001:  50%|█████     | 5/10 [00:00<00:00, 10.13it/s, Loss=0.278]
+Epoch 105/10001:  50%|█████     | 5/10 [00:00<00:00, 10.13it/s, Loss=0.276]
+Epoch 105/10001:  50%|█████     | 5/10 [00:00<00:00, 10.13it/s, Loss=0.281]
+Epoch 105/10001:  50%|█████     | 5/10 [00:00<00:00, 10.13it/s, Loss=0.279]
+Epoch 105/10001:  50%|█████     | 5/10 [00:00<00:00, 10.13it/s, Loss=0.274]
+Epoch 105/10001:  50%|█████     | 5/10 [00:00<00:00, 10.13it/s, Loss=0.275]
+Epoch 105/10001: 100%|██████████| 10/10 [00:00<00:00, 19.49it/s, Loss=0.275]
+Epoch 105/10001: 100%|██████████| 10/10 [00:00<00:00, 11.97it/s, Loss=0.275]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 106/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 106/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.281]
+Epoch 106/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.281]
+Epoch 106/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.268]
+Epoch 106/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.271]
+Epoch 106/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.284]
+Epoch 106/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.281]
+Epoch 106/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.271]
+Epoch 106/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.271]
+Epoch 106/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.28] 
+Epoch 106/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.285]
+Epoch 106/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.279]
+Epoch 106/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.271]
+Epoch 106/10001: 100%|██████████| 10/10 [00:00<00:00, 12.91it/s, Loss=0.271]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 107/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 107/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.281]
+Epoch 107/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.281]
+Epoch 107/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.281]
+Epoch 107/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.278]
+Epoch 107/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.28] 
+Epoch 107/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.283]
+Epoch 107/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.272]
+Epoch 107/10001:  60%|██████    | 6/10 [00:00<00:00, 14.70it/s, Loss=0.272]
+Epoch 107/10001:  60%|██████    | 6/10 [00:00<00:00, 14.70it/s, Loss=0.28] 
+Epoch 107/10001:  60%|██████    | 6/10 [00:00<00:00, 14.70it/s, Loss=0.279]
+Epoch 107/10001:  60%|██████    | 6/10 [00:00<00:00, 14.70it/s, Loss=0.277]
+Epoch 107/10001:  60%|██████    | 6/10 [00:00<00:00, 14.70it/s, Loss=0.287]
+Epoch 107/10001: 100%|██████████| 10/10 [00:00<00:00, 20.99it/s, Loss=0.287]
+Epoch 107/10001: 100%|██████████| 10/10 [00:00<00:00, 13.87it/s, Loss=0.287]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 108/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 108/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.279]
+Epoch 108/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.279]
+Epoch 108/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.276]
+Epoch 108/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.282]
+Epoch 108/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.28] 
+Epoch 108/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.278]
+Epoch 108/10001:  50%|█████     | 5/10 [00:00<00:00, 12.66it/s, Loss=0.278]
+Epoch 108/10001:  50%|█████     | 5/10 [00:00<00:00, 12.66it/s, Loss=0.281]
+Epoch 108/10001:  50%|█████     | 5/10 [00:00<00:00, 12.66it/s, Loss=0.277]
+Epoch 108/10001:  50%|█████     | 5/10 [00:00<00:00, 12.66it/s, Loss=0.273]
+Epoch 108/10001:  50%|█████     | 5/10 [00:00<00:00, 12.66it/s, Loss=0.27] 
+Epoch 108/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.26it/s, Loss=0.27]
+Epoch 108/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.26it/s, Loss=0.277]
+Epoch 108/10001: 100%|██████████| 10/10 [00:00<00:00, 13.50it/s, Loss=0.277]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 109/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 109/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.278]
+Epoch 109/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.278]
+Epoch 109/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.278]
+Epoch 109/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.275]
+Epoch 109/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.281]
+Epoch 109/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.268]
+Epoch 109/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.268]
+Epoch 109/10001:  60%|██████    | 6/10 [00:00<00:00, 15.79it/s, Loss=0.268]
+Epoch 109/10001:  60%|██████    | 6/10 [00:00<00:00, 15.79it/s, Loss=0.271]
+Epoch 109/10001:  60%|██████    | 6/10 [00:00<00:00, 15.79it/s, Loss=0.273]
+Epoch 109/10001:  60%|██████    | 6/10 [00:00<00:00, 15.79it/s, Loss=0.275]
+Epoch 109/10001:  60%|██████    | 6/10 [00:00<00:00, 15.79it/s, Loss=0.278]
+Epoch 109/10001: 100%|██████████| 10/10 [00:00<00:00, 15.46it/s, Loss=0.278]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 110/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 110/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.269]
+Epoch 110/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.269]
+Epoch 110/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.281]
+Epoch 110/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.282]
+Epoch 110/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.272]
+Epoch 110/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.271]
+Epoch 110/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.271]
+Epoch 110/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.268]
+Epoch 110/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.273]
+Epoch 110/10001:  80%|████████  | 8/10 [00:00<00:00, 19.42it/s, Loss=0.273]
+Epoch 110/10001:  80%|████████  | 8/10 [00:00<00:00, 19.42it/s, Loss=0.281]
+Epoch 110/10001:  80%|████████  | 8/10 [00:00<00:00, 19.42it/s, Loss=0.273]
+Epoch 110/10001: 100%|██████████| 10/10 [00:00<00:00, 15.05it/s, Loss=0.273]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 111/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 111/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.281]
+Epoch 111/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.281]
+Epoch 111/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.282]
+Epoch 111/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.278]
+Epoch 111/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.269]
+Epoch 111/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.268]
+Epoch 111/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.273]
+Epoch 111/10001:  60%|██████    | 6/10 [00:00<00:00, 14.85it/s, Loss=0.273]
+Epoch 111/10001:  60%|██████    | 6/10 [00:00<00:00, 14.85it/s, Loss=0.28] 
+Epoch 111/10001:  60%|██████    | 6/10 [00:00<00:00, 14.85it/s, Loss=0.276]
+Epoch 111/10001:  60%|██████    | 6/10 [00:00<00:00, 14.85it/s, Loss=0.279]
+Epoch 111/10001:  60%|██████    | 6/10 [00:00<00:00, 14.85it/s, Loss=0.264]
+Epoch 111/10001: 100%|██████████| 10/10 [00:00<00:00, 13.52it/s, Loss=0.264]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 112/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 112/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.277]
+Epoch 112/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.277]
+Epoch 112/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.274]
+Epoch 112/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.275]
+Epoch 112/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.281]
+Epoch 112/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.276]
+Epoch 112/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.273]
+Epoch 112/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.277]
+Epoch 112/10001:  70%|███████   | 7/10 [00:00<00:00, 15.86it/s, Loss=0.277]
+Epoch 112/10001:  70%|███████   | 7/10 [00:00<00:00, 15.86it/s, Loss=0.278]
+Epoch 112/10001:  70%|███████   | 7/10 [00:00<00:00, 15.86it/s, Loss=0.277]
+Epoch 112/10001:  70%|███████   | 7/10 [00:00<00:00, 15.86it/s, Loss=0.274]
+Epoch 112/10001: 100%|██████████| 10/10 [00:00<00:00, 13.90it/s, Loss=0.274]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 113/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 113/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.279]
+Epoch 113/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.279]
+Epoch 113/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.267]
+Epoch 113/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.271]
+Epoch 113/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.275]
+Epoch 113/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.277]
+Epoch 113/10001:  10%|█         | 1/10 [00:00<00:03,  2.47it/s, Loss=0.28] 
+Epoch 113/10001:  60%|██████    | 6/10 [00:00<00:00, 14.75it/s, Loss=0.28]
+Epoch 113/10001:  60%|██████    | 6/10 [00:00<00:00, 14.75it/s, Loss=0.268]
+Epoch 113/10001:  60%|██████    | 6/10 [00:00<00:00, 14.75it/s, Loss=0.279]
+Epoch 113/10001:  60%|██████    | 6/10 [00:00<00:00, 14.75it/s, Loss=0.279]
+Epoch 113/10001:  60%|██████    | 6/10 [00:00<00:00, 14.75it/s, Loss=0.272]
+Epoch 113/10001: 100%|██████████| 10/10 [00:00<00:00, 14.36it/s, Loss=0.272]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 114/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.267]
+Epoch 114/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.281]
+Epoch 114/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.269]
+Epoch 114/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.274]
+Epoch 114/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.274]
+Epoch 114/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.267]
+Epoch 114/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.269]
+Epoch 114/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.277]
+Epoch 114/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.278]
+Epoch 114/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.265]
+Epoch 114/10001:  40%|████      | 4/10 [00:00<00:00,  9.72it/s, Loss=0.275]
+Epoch 114/10001: 100%|██████████| 10/10 [00:00<00:00, 22.91it/s, Loss=0.275]
+Epoch 114/10001: 100%|██████████| 10/10 [00:00<00:00, 13.78it/s, Loss=0.275]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 115/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.274]
+Epoch 115/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.274]
+Epoch 115/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.281]
+Epoch 115/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.274]
+Epoch 115/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.271]
+Epoch 115/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.274]
+Epoch 115/10001:  50%|█████     | 5/10 [00:00<00:00, 12.00it/s, Loss=0.274]
+Epoch 115/10001:  50%|█████     | 5/10 [00:00<00:00, 12.00it/s, Loss=0.277]
+Epoch 115/10001:  50%|█████     | 5/10 [00:00<00:00, 12.00it/s, Loss=0.28] 
+Epoch 115/10001:  50%|█████     | 5/10 [00:00<00:00, 12.00it/s, Loss=0.276]
+Epoch 115/10001:  50%|█████     | 5/10 [00:00<00:00, 12.00it/s, Loss=0.273]
+Epoch 115/10001:  50%|█████     | 5/10 [00:00<00:00, 12.00it/s, Loss=0.275]
+Epoch 115/10001: 100%|██████████| 10/10 [00:00<00:00, 13.97it/s, Loss=0.275]
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 116/10001:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 116/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.278]
+Epoch 116/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.274]
+Epoch 116/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.278]
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+Epoch 116/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.272]
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+Epoch 116/10001:  50%|█████     | 5/10 [00:00<00:00, 13.08it/s, Loss=0.278]
+Epoch 116/10001:  50%|█████     | 5/10 [00:00<00:00, 13.08it/s, Loss=0.266]
+Epoch 116/10001:  50%|█████     | 5/10 [00:00<00:00, 13.08it/s, Loss=0.276]
+Epoch 116/10001:  50%|█████     | 5/10 [00:00<00:00, 13.08it/s, Loss=0.277]
+Epoch 116/10001:  50%|█████     | 5/10 [00:00<00:00, 13.08it/s, Loss=0.282]
+Epoch 116/10001: 100%|██████████| 10/10 [00:00<00:00, 15.08it/s, Loss=0.282]
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 117/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 117/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.279]
+Epoch 117/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.279]
+Epoch 117/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.273]
+Epoch 117/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.272]
+Epoch 117/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.27] 
+Epoch 117/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.272]
+Epoch 117/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.274]
+Epoch 117/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.267]
+Epoch 117/10001:  70%|███████   | 7/10 [00:00<00:00, 19.76it/s, Loss=0.267]
+Epoch 117/10001:  70%|███████   | 7/10 [00:00<00:00, 19.76it/s, Loss=0.275]
+Epoch 117/10001:  70%|███████   | 7/10 [00:00<00:00, 19.76it/s, Loss=0.272]
+Epoch 117/10001:  70%|███████   | 7/10 [00:00<00:00, 19.76it/s, Loss=0.277]
+Epoch 117/10001: 100%|██████████| 10/10 [00:00<00:00, 17.02it/s, Loss=0.277]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 118/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 118/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.278]
+Epoch 118/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.278]
+Epoch 118/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.267]
+Epoch 118/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.277]
+Epoch 118/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.275]
+Epoch 118/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.273]
+Epoch 118/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.272]
+Epoch 118/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.272]
+Epoch 118/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.273]
+Epoch 118/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.272]
+Epoch 118/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.268]
+Epoch 118/10001:  60%|██████    | 6/10 [00:00<00:00, 14.74it/s, Loss=0.27] 
+Epoch 118/10001: 100%|██████████| 10/10 [00:00<00:00, 21.14it/s, Loss=0.27]
+Epoch 118/10001: 100%|██████████| 10/10 [00:00<00:00, 13.59it/s, Loss=0.27]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 119/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.276]
+Epoch 119/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.263]
+Epoch 119/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.273]
+Epoch 119/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.273]
+Epoch 119/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.276]
+Epoch 119/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.281]
+Epoch 119/10001:  60%|██████    | 6/10 [00:00<00:00, 13.01it/s, Loss=0.281]
+Epoch 119/10001:  60%|██████    | 6/10 [00:00<00:00, 13.01it/s, Loss=0.271]
+Epoch 119/10001:  60%|██████    | 6/10 [00:00<00:00, 13.01it/s, Loss=0.272]
+Epoch 119/10001:  60%|██████    | 6/10 [00:00<00:00, 13.01it/s, Loss=0.27] 
+Epoch 119/10001:  60%|██████    | 6/10 [00:00<00:00, 13.01it/s, Loss=0.271]
+Epoch 119/10001: 100%|██████████| 10/10 [00:00<00:00, 12.63it/s, Loss=0.271]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 120/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.277]
+Epoch 120/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.269]
+Epoch 120/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.273]
+Epoch 120/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.272]
+Epoch 120/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.268]
+Epoch 120/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.275]
+Epoch 120/10001:  60%|██████    | 6/10 [00:00<00:00, 14.35it/s, Loss=0.275]
+Epoch 120/10001:  60%|██████    | 6/10 [00:00<00:00, 14.35it/s, Loss=0.269]
+Epoch 120/10001:  60%|██████    | 6/10 [00:00<00:00, 14.35it/s, Loss=0.27] 
+Epoch 120/10001:  60%|██████    | 6/10 [00:00<00:00, 14.35it/s, Loss=0.267]
+Epoch 120/10001:  60%|██████    | 6/10 [00:00<00:00, 14.35it/s, Loss=0.278]
+Epoch 120/10001: 100%|██████████| 10/10 [00:00<00:00, 14.04it/s, Loss=0.278]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 121/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.276]
+Epoch 121/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.277]
+Epoch 121/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.268]
+Epoch 121/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.267]
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+Epoch 121/10001:  50%|█████     | 5/10 [00:00<00:00, 11.04it/s, Loss=0.273]
+Epoch 121/10001:  50%|█████     | 5/10 [00:00<00:00, 11.04it/s, Loss=0.275]
+Epoch 121/10001:  50%|█████     | 5/10 [00:00<00:00, 11.04it/s, Loss=0.273]
+Epoch 121/10001:  50%|█████     | 5/10 [00:00<00:00, 11.04it/s, Loss=0.276]
+Epoch 121/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.30it/s, Loss=0.276]
+Epoch 121/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.30it/s, Loss=0.274]
+Epoch 121/10001: 100%|██████████| 10/10 [00:00<00:00, 12.18it/s, Loss=0.274]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 122/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.271]
+Epoch 122/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.271]
+Epoch 122/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.271]
+Epoch 122/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.274]
+Epoch 122/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.276]
+Epoch 122/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.272]
+Epoch 122/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.278]
+Epoch 122/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.278]
+Epoch 122/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.281]
+Epoch 122/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.273]
+Epoch 122/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.277]
+Epoch 122/10001:  60%|██████    | 6/10 [00:00<00:00, 13.43it/s, Loss=0.271]
+Epoch 122/10001: 100%|██████████| 10/10 [00:00<00:00, 12.93it/s, Loss=0.271]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 123/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 123/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.28]
+Epoch 123/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.28]
+Epoch 123/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.287]
+Epoch 123/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.273]
+Epoch 123/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.274]
+Epoch 123/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.267]
+Epoch 123/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.278]
+Epoch 123/10001:  60%|██████    | 6/10 [00:00<00:00, 13.63it/s, Loss=0.278]
+Epoch 123/10001:  60%|██████    | 6/10 [00:00<00:00, 13.63it/s, Loss=0.279]
+Epoch 123/10001:  60%|██████    | 6/10 [00:00<00:00, 13.63it/s, Loss=0.273]
+Epoch 123/10001:  60%|██████    | 6/10 [00:00<00:00, 13.63it/s, Loss=0.274]
+Epoch 123/10001:  60%|██████    | 6/10 [00:00<00:00, 13.63it/s, Loss=0.28] 
+Epoch 123/10001: 100%|██████████| 10/10 [00:00<00:00, 13.64it/s, Loss=0.28]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 124/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 124/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.275]
+Epoch 124/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.275]
+Epoch 124/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.275]
+Epoch 124/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.273]
+Epoch 124/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.276]
+Epoch 124/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.273]
+Epoch 124/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.271]
+Epoch 124/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.271]
+Epoch 124/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.283]
+Epoch 124/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.266]
+Epoch 124/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.275]
+Epoch 124/10001:  60%|██████    | 6/10 [00:00<00:00, 15.69it/s, Loss=0.277]
+Epoch 124/10001: 100%|██████████| 10/10 [00:00<00:00, 15.26it/s, Loss=0.277]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 125/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 125/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.28]
+Epoch 125/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.28]
+Epoch 125/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.274]
+Epoch 125/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.276]
+Epoch 125/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.267]
+Epoch 125/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.27] 
+Epoch 125/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.27]
+Epoch 125/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.263]
+Epoch 125/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.275]
+Epoch 125/10001:  80%|████████  | 8/10 [00:00<00:00, 20.28it/s, Loss=0.275]
+Epoch 125/10001:  80%|████████  | 8/10 [00:00<00:00, 20.28it/s, Loss=0.277]
+Epoch 125/10001:  80%|████████  | 8/10 [00:00<00:00, 20.28it/s, Loss=0.275]
+Epoch 125/10001: 100%|██████████| 10/10 [00:00<00:00, 15.32it/s, Loss=0.275]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 126/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 126/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.273]
+Epoch 126/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.273]
+Epoch 126/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.276]
+Epoch 126/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.276]
+Epoch 126/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.266]
+Epoch 126/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.265]
+Epoch 126/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.265]
+Epoch 126/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.265]
+Epoch 126/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.279]
+Epoch 126/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.27] 
+Epoch 126/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.271]
+Epoch 126/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.267]
+Epoch 126/10001: 100%|██████████| 10/10 [00:00<00:00, 13.19it/s, Loss=0.267]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 127/10001:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 127/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.276]
+Epoch 127/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.264]
+Epoch 127/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.276]
+Epoch 127/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.279]
+Epoch 127/10001:  40%|████      | 4/10 [00:00<00:00,  9.44it/s, Loss=0.279]
+Epoch 127/10001:  40%|████      | 4/10 [00:00<00:00,  9.44it/s, Loss=0.272]
+Epoch 127/10001:  40%|████      | 4/10 [00:00<00:00,  9.44it/s, Loss=0.277]
+Epoch 127/10001:  40%|████      | 4/10 [00:00<00:00,  9.44it/s, Loss=0.276]
+Epoch 127/10001:  40%|████      | 4/10 [00:00<00:00,  9.44it/s, Loss=0.276]
+Epoch 127/10001:  80%|████████  | 8/10 [00:00<00:00, 17.07it/s, Loss=0.276]
+Epoch 127/10001:  80%|████████  | 8/10 [00:00<00:00, 17.07it/s, Loss=0.271]
+Epoch 127/10001:  80%|████████  | 8/10 [00:00<00:00, 17.07it/s, Loss=0.274]
+Epoch 127/10001: 100%|██████████| 10/10 [00:00<00:00, 11.84it/s, Loss=0.274]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 128/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 128/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.276]
+Epoch 128/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.276]
+Epoch 128/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.271]
+Epoch 128/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.275]
+Epoch 128/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.274]
+Epoch 128/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.271]
+Epoch 128/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.274]
+Epoch 128/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.274]
+Epoch 128/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.271]
+Epoch 128/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.277]
+Epoch 128/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.274]
+Epoch 128/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.265]
+Epoch 128/10001: 100%|██████████| 10/10 [00:00<00:00, 13.60it/s, Loss=0.265]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 129/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 129/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.267]
+Epoch 129/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.267]
+Epoch 129/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.275]
+Epoch 129/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.27] 
+Epoch 129/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.27]
+Epoch 129/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.268]
+Epoch 129/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.275]
+Epoch 129/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.275]
+Epoch 129/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.277]
+Epoch 129/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.269]
+Epoch 129/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.273]
+Epoch 129/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.27] 
+Epoch 129/10001: 100%|██████████| 10/10 [00:00<00:00, 14.07it/s, Loss=0.27]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 130/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 130/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.276]
+Epoch 130/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.276]
+Epoch 130/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.274]
+Epoch 130/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.269]
+Epoch 130/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.269]
+Epoch 130/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.266]
+Epoch 130/10001:  50%|█████     | 5/10 [00:00<00:00, 12.76it/s, Loss=0.266]
+Epoch 130/10001:  50%|█████     | 5/10 [00:00<00:00, 12.76it/s, Loss=0.274]
+Epoch 130/10001:  50%|█████     | 5/10 [00:00<00:00, 12.76it/s, Loss=0.272]
+Epoch 130/10001:  50%|█████     | 5/10 [00:00<00:00, 12.76it/s, Loss=0.273]
+Epoch 130/10001:  50%|█████     | 5/10 [00:00<00:00, 12.76it/s, Loss=0.275]
+Epoch 130/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.81it/s, Loss=0.275]
+Epoch 130/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.81it/s, Loss=0.272]
+Epoch 130/10001: 100%|██████████| 10/10 [00:00<00:00, 14.04it/s, Loss=0.272]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 131/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 131/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.273]
+Epoch 131/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.273]
+Epoch 131/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.282]
+Epoch 131/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.27] 
+Epoch 131/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.274]
+Epoch 131/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.274]
+Epoch 131/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.268]
+Epoch 131/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.272]
+Epoch 131/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.266]
+Epoch 131/10001:  80%|████████  | 8/10 [00:00<00:00, 20.61it/s, Loss=0.266]
+Epoch 131/10001:  80%|████████  | 8/10 [00:00<00:00, 20.61it/s, Loss=0.275]
+Epoch 131/10001:  80%|████████  | 8/10 [00:00<00:00, 20.61it/s, Loss=0.274]
+Epoch 131/10001: 100%|██████████| 10/10 [00:00<00:00, 15.72it/s, Loss=0.274]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 132/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 132/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.276]
+Epoch 132/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.276]
+Epoch 132/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.274]
+Epoch 132/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.271]
+Epoch 132/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.278]
+Epoch 132/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.274]
+Epoch 132/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.267]
+Epoch 132/10001:  60%|██████    | 6/10 [00:00<00:00, 16.92it/s, Loss=0.267]
+Epoch 132/10001:  60%|██████    | 6/10 [00:00<00:00, 16.92it/s, Loss=0.27] 
+Epoch 132/10001:  60%|██████    | 6/10 [00:00<00:00, 16.92it/s, Loss=0.279]
+Epoch 132/10001:  60%|██████    | 6/10 [00:00<00:00, 16.92it/s, Loss=0.279]
+Epoch 132/10001:  60%|██████    | 6/10 [00:00<00:00, 16.92it/s, Loss=0.267]
+Epoch 132/10001: 100%|██████████| 10/10 [00:00<00:00, 16.61it/s, Loss=0.267]
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 133/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 133/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.272]
+Epoch 133/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.272]
+Epoch 133/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.274]
+Epoch 133/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.274]
+Epoch 133/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.277]
+Epoch 133/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.273]
+Epoch 133/10001:  50%|█████     | 5/10 [00:00<00:00, 11.02it/s, Loss=0.273]
+Epoch 133/10001:  50%|█████     | 5/10 [00:00<00:00, 11.02it/s, Loss=0.28] 
+Epoch 133/10001:  50%|█████     | 5/10 [00:00<00:00, 11.02it/s, Loss=0.273]
+Epoch 133/10001:  50%|█████     | 5/10 [00:00<00:00, 11.02it/s, Loss=0.277]
+Epoch 133/10001:  50%|█████     | 5/10 [00:00<00:00, 11.02it/s, Loss=0.279]
+Epoch 133/10001:  50%|█████     | 5/10 [00:00<00:00, 11.02it/s, Loss=0.277]
+Epoch 133/10001: 100%|██████████| 10/10 [00:00<00:00, 13.06it/s, Loss=0.277]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 134/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 134/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.276]
+Epoch 134/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.276]
+Epoch 134/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.273]
+Epoch 134/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.28] 
+Epoch 134/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.297]
+Epoch 134/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.287]
+Epoch 134/10001:  50%|█████     | 5/10 [00:00<00:00, 13.46it/s, Loss=0.287]
+Epoch 134/10001:  50%|█████     | 5/10 [00:00<00:00, 13.46it/s, Loss=0.318]
+Epoch 134/10001:  50%|█████     | 5/10 [00:00<00:00, 13.46it/s, Loss=0.381]
+Epoch 134/10001:  50%|█████     | 5/10 [00:00<00:00, 13.46it/s, Loss=0.545]
+Epoch 134/10001:  50%|█████     | 5/10 [00:00<00:00, 13.46it/s, Loss=0.463]
+Epoch 134/10001:  50%|█████     | 5/10 [00:00<00:00, 13.46it/s, Loss=0.463]
+Epoch 134/10001: 100%|██████████| 10/10 [00:00<00:00, 15.09it/s, Loss=0.463]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 135/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 135/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.69]
+Epoch 135/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.69]
+Epoch 135/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.82]
+Epoch 135/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.862]
+Epoch 135/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.868]
+Epoch 135/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=1.52] 
+Epoch 135/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.891]
+Epoch 135/10001:  60%|██████    | 6/10 [00:00<00:00, 16.75it/s, Loss=0.891]
+Epoch 135/10001:  60%|██████    | 6/10 [00:00<00:00, 16.75it/s, Loss=1.22] 
+Epoch 135/10001:  60%|██████    | 6/10 [00:00<00:00, 16.75it/s, Loss=1.29]
+Epoch 135/10001:  60%|██████    | 6/10 [00:00<00:00, 16.75it/s, Loss=0.991]
+Epoch 135/10001:  60%|██████    | 6/10 [00:00<00:00, 16.75it/s, Loss=0.888]
+Epoch 135/10001: 100%|██████████| 10/10 [00:00<00:00, 22.49it/s, Loss=0.888]
+Epoch 135/10001: 100%|██████████| 10/10 [00:00<00:00, 14.73it/s, Loss=0.888]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 136/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 136/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=1.36]
+Epoch 136/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=1.36]
+Epoch 136/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=4.18]
+Epoch 136/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.958]
+Epoch 136/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=4.36] 
+Epoch 136/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=1.26]
+Epoch 136/10001:  50%|█████     | 5/10 [00:00<00:00, 11.17it/s, Loss=1.26]
+Epoch 136/10001:  50%|█████     | 5/10 [00:00<00:00, 11.17it/s, Loss=0.996]
+Epoch 136/10001:  50%|█████     | 5/10 [00:00<00:00, 11.17it/s, Loss=0.936]
+Epoch 136/10001:  50%|█████     | 5/10 [00:00<00:00, 11.17it/s, Loss=0.984]
+Epoch 136/10001:  50%|█████     | 5/10 [00:00<00:00, 11.17it/s, Loss=0.852]
+Epoch 136/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.32it/s, Loss=0.852]
+Epoch 136/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.32it/s, Loss=0.949]
+Epoch 136/10001: 100%|██████████| 10/10 [00:00<00:00, 12.43it/s, Loss=0.949]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 137/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 137/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=1.16]
+Epoch 137/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=1.16]
+Epoch 137/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=1.01]
+Epoch 137/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=1.18]
+Epoch 137/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=1.26]
+Epoch 137/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.85]
+Epoch 137/10001:  50%|█████     | 5/10 [00:00<00:00, 12.59it/s, Loss=0.85]
+Epoch 137/10001:  50%|█████     | 5/10 [00:00<00:00, 12.59it/s, Loss=0.866]
+Epoch 137/10001:  50%|█████     | 5/10 [00:00<00:00, 12.59it/s, Loss=0.94] 
+Epoch 137/10001:  50%|█████     | 5/10 [00:00<00:00, 12.59it/s, Loss=2.82]
+Epoch 137/10001:  50%|█████     | 5/10 [00:00<00:00, 12.59it/s, Loss=1.72]
+Epoch 137/10001:  50%|█████     | 5/10 [00:00<00:00, 12.59it/s, Loss=2.95]
+Epoch 137/10001: 100%|██████████| 10/10 [00:00<00:00, 21.85it/s, Loss=2.95]
+Epoch 137/10001: 100%|██████████| 10/10 [00:00<00:00, 14.19it/s, Loss=2.95]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 138/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 138/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.859]
+Epoch 138/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.859]
+Epoch 138/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.872]
+Epoch 138/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.851]
+Epoch 138/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.849]
+Epoch 138/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=1.81] 
+Epoch 138/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.857]
+Epoch 138/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.843]
+Epoch 138/10001:  70%|███████   | 7/10 [00:00<00:00, 17.68it/s, Loss=0.843]
+Epoch 138/10001:  70%|███████   | 7/10 [00:00<00:00, 17.68it/s, Loss=0.853]
+Epoch 138/10001:  70%|███████   | 7/10 [00:00<00:00, 17.68it/s, Loss=0.841]
+Epoch 138/10001:  70%|███████   | 7/10 [00:00<00:00, 17.68it/s, Loss=0.853]
+Epoch 138/10001: 100%|██████████| 10/10 [00:00<00:00, 14.64it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 139/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 139/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 139/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.846]
+Epoch 139/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.855]
+Epoch 139/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.844]
+Epoch 139/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.849]
+Epoch 139/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.849]
+Epoch 139/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.857]
+Epoch 139/10001:  60%|██████    | 6/10 [00:00<00:00, 13.32it/s, Loss=0.857]
+Epoch 139/10001:  60%|██████    | 6/10 [00:00<00:00, 13.32it/s, Loss=0.838]
+Epoch 139/10001:  60%|██████    | 6/10 [00:00<00:00, 13.32it/s, Loss=0.846]
+Epoch 139/10001:  60%|██████    | 6/10 [00:00<00:00, 13.32it/s, Loss=1.23] 
+Epoch 139/10001:  60%|██████    | 6/10 [00:00<00:00, 13.32it/s, Loss=0.853]
+Epoch 139/10001: 100%|██████████| 10/10 [00:00<00:00, 12.97it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 140/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 140/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 140/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.85]
+Epoch 140/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=3.82]
+Epoch 140/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.854]
+Epoch 140/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.859]
+Epoch 140/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.854]
+Epoch 140/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.854]
+Epoch 140/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.843]
+Epoch 140/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.864]
+Epoch 140/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.85] 
+Epoch 140/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.846]
+Epoch 140/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.49it/s, Loss=0.846]
+Epoch 140/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.49it/s, Loss=0.853]
+Epoch 140/10001: 100%|██████████| 10/10 [00:00<00:00, 12.99it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 141/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 141/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 141/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.847]
+Epoch 141/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.885]
+Epoch 141/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.846]
+Epoch 141/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.852]
+Epoch 141/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.854]
+Epoch 141/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.847]
+Epoch 141/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.847]
+Epoch 141/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.857]
+Epoch 141/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.854]
+Epoch 141/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.848]
+Epoch 141/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.85] 
+Epoch 141/10001: 100%|██████████| 10/10 [00:00<00:00, 13.41it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 142/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 142/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 142/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.854]
+Epoch 142/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.85] 
+Epoch 142/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.848]
+Epoch 142/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.852]
+Epoch 142/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.839]
+Epoch 142/10001:  50%|█████     | 5/10 [00:00<00:00, 12.36it/s, Loss=0.839]
+Epoch 142/10001:  50%|█████     | 5/10 [00:00<00:00, 12.36it/s, Loss=0.857]
+Epoch 142/10001:  50%|█████     | 5/10 [00:00<00:00, 12.36it/s, Loss=0.85] 
+Epoch 142/10001:  50%|█████     | 5/10 [00:00<00:00, 12.36it/s, Loss=0.855]
+Epoch 142/10001:  50%|█████     | 5/10 [00:00<00:00, 12.36it/s, Loss=0.846]
+Epoch 142/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.36it/s, Loss=0.846]
+Epoch 142/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.36it/s, Loss=0.853]
+Epoch 142/10001: 100%|██████████| 10/10 [00:00<00:00, 13.49it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 143/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 143/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 143/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.849]
+Epoch 143/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.855]
+Epoch 143/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 143/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.851]
+Epoch 143/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.851]
+Epoch 143/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.852]
+Epoch 143/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.85] 
+Epoch 143/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.856]
+Epoch 143/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.847]
+Epoch 143/10001:  80%|████████  | 8/10 [00:00<00:00, 16.37it/s, Loss=0.847]
+Epoch 143/10001:  80%|████████  | 8/10 [00:00<00:00, 16.37it/s, Loss=0.852]
+Epoch 143/10001:  80%|████████  | 8/10 [00:00<00:00, 16.37it/s, Loss=0.856]
+Epoch 143/10001: 100%|██████████| 10/10 [00:00<00:00, 12.16it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 144/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 144/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 144/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.846]
+Epoch 144/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.853]
+Epoch 144/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.853]
+Epoch 144/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.854]
+Epoch 144/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.846]
+Epoch 144/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.85] 
+Epoch 144/10001:  60%|██████    | 6/10 [00:00<00:00, 15.25it/s, Loss=0.85]
+Epoch 144/10001:  60%|██████    | 6/10 [00:00<00:00, 15.25it/s, Loss=0.852]
+Epoch 144/10001:  60%|██████    | 6/10 [00:00<00:00, 15.25it/s, Loss=0.853]
+Epoch 144/10001:  60%|██████    | 6/10 [00:00<00:00, 15.25it/s, Loss=0.849]
+Epoch 144/10001:  60%|██████    | 6/10 [00:00<00:00, 15.25it/s, Loss=0.851]
+Epoch 144/10001: 100%|██████████| 10/10 [00:00<00:00, 14.58it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 145/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 145/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 145/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.853]
+Epoch 145/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.854]
+Epoch 145/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.851]
+Epoch 145/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.847]
+Epoch 145/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.852]
+Epoch 145/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.852]
+Epoch 145/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.849]
+Epoch 145/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.849]
+Epoch 145/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.857]
+Epoch 145/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.854]
+Epoch 145/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.853]
+Epoch 145/10001: 100%|██████████| 10/10 [00:00<00:00, 22.68it/s, Loss=0.853]
+Epoch 145/10001: 100%|██████████| 10/10 [00:00<00:00, 14.22it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 146/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 146/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 146/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.847]
+Epoch 146/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.851]
+Epoch 146/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.859]
+Epoch 146/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.852]
+Epoch 146/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.854]
+Epoch 146/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.85] 
+Epoch 146/10001:  60%|██████    | 6/10 [00:00<00:00, 16.82it/s, Loss=0.85]
+Epoch 146/10001:  60%|██████    | 6/10 [00:00<00:00, 16.82it/s, Loss=0.851]
+Epoch 146/10001:  60%|██████    | 6/10 [00:00<00:00, 16.82it/s, Loss=0.848]
+Epoch 146/10001:  60%|██████    | 6/10 [00:00<00:00, 16.82it/s, Loss=0.844]
+Epoch 146/10001:  60%|██████    | 6/10 [00:00<00:00, 16.82it/s, Loss=0.857]
+Epoch 146/10001: 100%|██████████| 10/10 [00:00<00:00, 23.34it/s, Loss=0.857]
+Epoch 146/10001: 100%|██████████| 10/10 [00:00<00:00, 15.29it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 147/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 147/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 147/10001:  10%|█         | 1/10 [00:00<00:02,  3.21it/s, Loss=0.85]
+Epoch 147/10001:  10%|█         | 1/10 [00:00<00:02,  3.21it/s, Loss=0.853]
+Epoch 147/10001:  10%|█         | 1/10 [00:00<00:02,  3.21it/s, Loss=0.851]
+Epoch 147/10001:  10%|█         | 1/10 [00:00<00:02,  3.21it/s, Loss=0.843]
+Epoch 147/10001:  10%|█         | 1/10 [00:00<00:02,  3.21it/s, Loss=0.845]
+Epoch 147/10001:  10%|█         | 1/10 [00:00<00:02,  3.21it/s, Loss=0.849]
+Epoch 147/10001:  60%|██████    | 6/10 [00:00<00:00, 17.50it/s, Loss=0.849]
+Epoch 147/10001:  60%|██████    | 6/10 [00:00<00:00, 17.50it/s, Loss=0.851]
+Epoch 147/10001:  60%|██████    | 6/10 [00:00<00:00, 17.50it/s, Loss=0.847]
+Epoch 147/10001:  60%|██████    | 6/10 [00:00<00:00, 17.50it/s, Loss=0.856]
+Epoch 147/10001:  60%|██████    | 6/10 [00:00<00:00, 17.50it/s, Loss=0.855]
+Epoch 147/10001: 100%|██████████| 10/10 [00:00<00:00, 15.21it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 148/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 148/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 148/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.85]
+Epoch 148/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.857]
+Epoch 148/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.85] 
+Epoch 148/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.851]
+Epoch 148/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.848]
+Epoch 148/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.858]
+Epoch 148/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.858]
+Epoch 148/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.849]
+Epoch 148/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.852]
+Epoch 148/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.859]
+Epoch 148/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.847]
+Epoch 148/10001: 100%|██████████| 10/10 [00:00<00:00, 13.40it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 149/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 149/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 149/10001:  10%|█         | 1/10 [00:00<00:03,  2.76it/s, Loss=0.854]
+Epoch 149/10001:  10%|█         | 1/10 [00:00<00:03,  2.76it/s, Loss=0.846]
+Epoch 149/10001:  10%|█         | 1/10 [00:00<00:03,  2.76it/s, Loss=0.847]
+Epoch 149/10001:  10%|█         | 1/10 [00:00<00:03,  2.76it/s, Loss=0.852]
+Epoch 149/10001:  10%|█         | 1/10 [00:00<00:03,  2.76it/s, Loss=0.851]
+Epoch 149/10001:  10%|█         | 1/10 [00:00<00:03,  2.76it/s, Loss=0.85] 
+Epoch 149/10001:  60%|██████    | 6/10 [00:00<00:00, 15.78it/s, Loss=0.85]
+Epoch 149/10001:  60%|██████    | 6/10 [00:00<00:00, 15.78it/s, Loss=0.856]
+Epoch 149/10001:  60%|██████    | 6/10 [00:00<00:00, 15.78it/s, Loss=0.852]
+Epoch 149/10001:  60%|██████    | 6/10 [00:00<00:00, 15.78it/s, Loss=0.853]
+Epoch 149/10001:  60%|██████    | 6/10 [00:00<00:00, 15.78it/s, Loss=0.855]
+Epoch 149/10001: 100%|██████████| 10/10 [00:00<00:00, 15.27it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 150/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 150/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.861]
+Epoch 150/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.861]
+Epoch 150/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.857]
+Epoch 150/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.853]
+Epoch 150/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.851]
+Epoch 150/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.851]
+Epoch 150/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.853]
+Epoch 150/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.858]
+Epoch 150/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.853]
+Epoch 150/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.842]
+Epoch 150/10001:  90%|█████████ | 9/10 [00:00<00:00, 24.10it/s, Loss=0.842]
+Epoch 150/10001:  90%|█████████ | 9/10 [00:00<00:00, 24.10it/s, Loss=0.847]
+Epoch 150/10001: 100%|██████████| 10/10 [00:00<00:00, 16.68it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 151/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 151/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 151/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.851]
+Epoch 151/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.854]
+Epoch 151/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.847]
+Epoch 151/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.853]
+Epoch 151/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.849]
+Epoch 151/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.851]
+Epoch 151/10001:  60%|██████    | 6/10 [00:00<00:00, 15.31it/s, Loss=0.851]
+Epoch 151/10001:  60%|██████    | 6/10 [00:00<00:00, 15.31it/s, Loss=0.852]
+Epoch 151/10001:  60%|██████    | 6/10 [00:00<00:00, 15.31it/s, Loss=0.853]
+Epoch 151/10001:  60%|██████    | 6/10 [00:00<00:00, 15.31it/s, Loss=0.855]
+Epoch 151/10001:  60%|██████    | 6/10 [00:00<00:00, 15.31it/s, Loss=0.853]
+Epoch 151/10001: 100%|██████████| 10/10 [00:00<00:00, 14.12it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 152/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 152/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 152/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.852]
+Epoch 152/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.849]
+Epoch 152/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.846]
+Epoch 152/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.852]
+Epoch 152/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.857]
+Epoch 152/10001:  50%|█████     | 5/10 [00:00<00:00, 11.10it/s, Loss=0.857]
+Epoch 152/10001:  50%|█████     | 5/10 [00:00<00:00, 11.10it/s, Loss=0.854]
+Epoch 152/10001:  50%|█████     | 5/10 [00:00<00:00, 11.10it/s, Loss=0.846]
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+Epoch 152/10001: 100%|██████████| 10/10 [00:00<00:00, 20.76it/s, Loss=0.855]
+Epoch 152/10001: 100%|██████████| 10/10 [00:00<00:00, 13.04it/s, Loss=0.855]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 153/10001: 100%|██████████| 10/10 [00:00<00:00, 24.12it/s, Loss=0.849]
+Epoch 153/10001: 100%|██████████| 10/10 [00:00<00:00, 15.37it/s, Loss=0.849]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 154/10001:  60%|██████    | 6/10 [00:00<00:00, 17.29it/s, Loss=0.853]
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+Epoch 154/10001: 100%|██████████| 10/10 [00:00<00:00, 15.73it/s, Loss=0.85]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 155/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.08it/s, Loss=0.846]
+Epoch 155/10001: 100%|██████████| 10/10 [00:00<00:00, 12.52it/s, Loss=0.846]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 156/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.86] 
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+Epoch 156/10001:  60%|██████    | 6/10 [00:00<00:00, 15.68it/s, Loss=0.851]
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+Epoch 156/10001:  60%|██████    | 6/10 [00:00<00:00, 15.68it/s, Loss=0.848]
+Epoch 156/10001:  60%|██████    | 6/10 [00:00<00:00, 15.68it/s, Loss=0.857]
+Epoch 156/10001: 100%|██████████| 10/10 [00:00<00:00, 14.92it/s, Loss=0.857]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 157/10001:  50%|█████     | 5/10 [00:00<00:00, 12.80it/s, Loss=0.843]
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+Epoch 157/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.00it/s, Loss=0.845]
+Epoch 157/10001: 100%|██████████| 10/10 [00:00<00:00, 13.65it/s, Loss=0.845]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 160/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.46it/s, Loss=0.849]
+Epoch 160/10001: 100%|██████████| 10/10 [00:00<00:00, 14.33it/s, Loss=0.849]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 162/10001: 100%|██████████| 10/10 [00:00<00:00, 16.06it/s, Loss=0.858]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 165/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.854]
+Epoch 165/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.855]
+Epoch 165/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.855]
+Epoch 165/10001:  50%|█████     | 5/10 [00:00<00:00, 11.21it/s, Loss=0.855]
+Epoch 165/10001:  50%|█████     | 5/10 [00:00<00:00, 11.21it/s, Loss=0.849]
+Epoch 165/10001:  50%|█████     | 5/10 [00:00<00:00, 11.21it/s, Loss=0.845]
+Epoch 165/10001:  50%|█████     | 5/10 [00:00<00:00, 11.21it/s, Loss=0.851]
+Epoch 165/10001:  50%|█████     | 5/10 [00:00<00:00, 11.21it/s, Loss=0.853]
+Epoch 165/10001:  50%|█████     | 5/10 [00:00<00:00, 11.21it/s, Loss=0.849]
+Epoch 165/10001: 100%|██████████| 10/10 [00:00<00:00, 19.92it/s, Loss=0.849]
+Epoch 165/10001: 100%|██████████| 10/10 [00:00<00:00, 12.82it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 166/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 166/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 166/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 166/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.854]
+Epoch 166/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.854]
+Epoch 166/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.85] 
+Epoch 166/10001:  40%|████      | 4/10 [00:00<00:00,  8.89it/s, Loss=0.85]
+Epoch 166/10001:  40%|████      | 4/10 [00:00<00:00,  8.89it/s, Loss=0.847]
+Epoch 166/10001:  40%|████      | 4/10 [00:00<00:00,  8.89it/s, Loss=0.841]
+Epoch 166/10001:  40%|████      | 4/10 [00:00<00:00,  8.89it/s, Loss=0.843]
+Epoch 166/10001:  40%|████      | 4/10 [00:00<00:00,  8.89it/s, Loss=0.848]
+Epoch 166/10001:  80%|████████  | 8/10 [00:00<00:00, 16.43it/s, Loss=0.848]
+Epoch 166/10001:  80%|████████  | 8/10 [00:00<00:00, 16.43it/s, Loss=0.848]
+Epoch 166/10001:  80%|████████  | 8/10 [00:00<00:00, 16.43it/s, Loss=0.854]
+Epoch 166/10001: 100%|██████████| 10/10 [00:00<00:00, 11.97it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 167/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 167/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 167/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.853]
+Epoch 167/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.856]
+Epoch 167/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.856]
+Epoch 167/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.854]
+Epoch 167/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.851]
+Epoch 167/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.848]
+Epoch 167/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.858]
+Epoch 167/10001:  70%|███████   | 7/10 [00:00<00:00, 16.30it/s, Loss=0.858]
+Epoch 167/10001:  70%|███████   | 7/10 [00:00<00:00, 16.30it/s, Loss=0.854]
+Epoch 167/10001:  70%|███████   | 7/10 [00:00<00:00, 16.30it/s, Loss=0.855]
+Epoch 167/10001:  70%|███████   | 7/10 [00:00<00:00, 16.30it/s, Loss=0.855]
+Epoch 167/10001: 100%|██████████| 10/10 [00:00<00:00, 13.99it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 168/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 168/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 168/10001:  10%|█         | 1/10 [00:00<00:02,  3.16it/s, Loss=0.847]
+Epoch 168/10001:  10%|█         | 1/10 [00:00<00:02,  3.16it/s, Loss=0.848]
+Epoch 168/10001:  10%|█         | 1/10 [00:00<00:02,  3.16it/s, Loss=0.854]
+Epoch 168/10001:  10%|█         | 1/10 [00:00<00:02,  3.16it/s, Loss=0.853]
+Epoch 168/10001:  10%|█         | 1/10 [00:00<00:02,  3.16it/s, Loss=0.855]
+Epoch 168/10001:  10%|█         | 1/10 [00:00<00:02,  3.16it/s, Loss=0.857]
+Epoch 168/10001:  10%|█         | 1/10 [00:00<00:02,  3.16it/s, Loss=0.853]
+Epoch 168/10001:  70%|███████   | 7/10 [00:00<00:00, 19.81it/s, Loss=0.853]
+Epoch 168/10001:  70%|███████   | 7/10 [00:00<00:00, 19.81it/s, Loss=0.854]
+Epoch 168/10001:  70%|███████   | 7/10 [00:00<00:00, 19.81it/s, Loss=0.848]
+Epoch 168/10001:  70%|███████   | 7/10 [00:00<00:00, 19.81it/s, Loss=0.852]
+Epoch 168/10001: 100%|██████████| 10/10 [00:00<00:00, 16.58it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 169/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 169/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 169/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.855]
+Epoch 169/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.854]
+Epoch 169/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.851]
+Epoch 169/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.855]
+Epoch 169/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.844]
+Epoch 169/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.859]
+Epoch 169/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.849]
+Epoch 169/10001:  10%|█         | 1/10 [00:00<00:03,  2.96it/s, Loss=0.853]
+Epoch 169/10001:  80%|████████  | 8/10 [00:00<00:00, 22.56it/s, Loss=0.853]
+Epoch 169/10001:  80%|████████  | 8/10 [00:00<00:00, 22.56it/s, Loss=0.84] 
+Epoch 169/10001:  80%|████████  | 8/10 [00:00<00:00, 22.56it/s, Loss=0.861]
+Epoch 169/10001: 100%|██████████| 10/10 [00:00<00:00, 17.11it/s, Loss=0.861]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 170/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 170/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 170/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.852]
+Epoch 170/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.856]
+Epoch 170/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.854]
+Epoch 170/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.855]
+Epoch 170/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.848]
+Epoch 170/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.858]
+Epoch 170/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.849]
+Epoch 170/10001:  70%|███████   | 7/10 [00:00<00:00, 19.17it/s, Loss=0.849]
+Epoch 170/10001:  70%|███████   | 7/10 [00:00<00:00, 19.17it/s, Loss=0.849]
+Epoch 170/10001:  70%|███████   | 7/10 [00:00<00:00, 19.17it/s, Loss=0.846]
+Epoch 170/10001:  70%|███████   | 7/10 [00:00<00:00, 19.17it/s, Loss=0.85] 
+Epoch 170/10001: 100%|██████████| 10/10 [00:00<00:00, 15.91it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 171/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 171/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 171/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.848]
+Epoch 171/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.853]
+Epoch 171/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.844]
+Epoch 171/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.852]
+Epoch 171/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.851]
+Epoch 171/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.852]
+Epoch 171/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.85] 
+Epoch 171/10001:  70%|███████   | 7/10 [00:00<00:00, 18.89it/s, Loss=0.85]
+Epoch 171/10001:  70%|███████   | 7/10 [00:00<00:00, 18.89it/s, Loss=0.855]
+Epoch 171/10001:  70%|███████   | 7/10 [00:00<00:00, 18.89it/s, Loss=0.856]
+Epoch 171/10001:  70%|███████   | 7/10 [00:00<00:00, 18.89it/s, Loss=0.854]
+Epoch 171/10001: 100%|██████████| 10/10 [00:00<00:00, 15.02it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 172/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 172/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 172/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.855]
+Epoch 172/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.857]
+Epoch 172/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.853]
+Epoch 172/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.848]
+Epoch 172/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.856]
+Epoch 172/10001:  50%|█████     | 5/10 [00:00<00:00, 10.87it/s, Loss=0.856]
+Epoch 172/10001:  50%|█████     | 5/10 [00:00<00:00, 10.87it/s, Loss=0.86] 
+Epoch 172/10001:  50%|█████     | 5/10 [00:00<00:00, 10.87it/s, Loss=0.846]
+Epoch 172/10001:  50%|█████     | 5/10 [00:00<00:00, 10.87it/s, Loss=0.847]
+Epoch 172/10001:  50%|█████     | 5/10 [00:00<00:00, 10.87it/s, Loss=0.856]
+Epoch 172/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.83it/s, Loss=0.856]
+Epoch 172/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.83it/s, Loss=0.852]
+Epoch 172/10001: 100%|██████████| 10/10 [00:00<00:00, 12.57it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 173/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 173/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 173/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.852]
+Epoch 173/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.848]
+Epoch 173/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.853]
+Epoch 173/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.852]
+Epoch 173/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.851]
+Epoch 173/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.851]
+Epoch 173/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.862]
+Epoch 173/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.85] 
+Epoch 173/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.852]
+Epoch 173/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.849]
+Epoch 173/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.24it/s, Loss=0.849]
+Epoch 173/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.24it/s, Loss=0.85] 
+Epoch 173/10001: 100%|██████████| 10/10 [00:00<00:00, 12.68it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 174/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 174/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 174/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.843]
+Epoch 174/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 174/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 174/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.849]
+Epoch 174/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.858]
+Epoch 174/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 174/10001:  60%|██████    | 6/10 [00:00<00:00, 14.10it/s, Loss=0.854]
+Epoch 174/10001:  60%|██████    | 6/10 [00:00<00:00, 14.10it/s, Loss=0.854]
+Epoch 174/10001:  60%|██████    | 6/10 [00:00<00:00, 14.10it/s, Loss=0.849]
+Epoch 174/10001:  60%|██████    | 6/10 [00:00<00:00, 14.10it/s, Loss=0.846]
+Epoch 174/10001:  60%|██████    | 6/10 [00:00<00:00, 14.10it/s, Loss=0.843]
+Epoch 174/10001: 100%|██████████| 10/10 [00:00<00:00, 13.92it/s, Loss=0.843]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 175/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 175/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 175/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.85]
+Epoch 175/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.849]
+Epoch 175/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.849]
+Epoch 175/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.85] 
+Epoch 175/10001:  10%|█         | 1/10 [00:00<00:02,  3.17it/s, Loss=0.845]
+Epoch 175/10001:  50%|█████     | 5/10 [00:00<00:00, 13.73it/s, Loss=0.845]
+Epoch 175/10001:  50%|█████     | 5/10 [00:00<00:00, 13.73it/s, Loss=0.847]
+Epoch 175/10001:  50%|█████     | 5/10 [00:00<00:00, 13.73it/s, Loss=0.848]
+Epoch 175/10001:  50%|█████     | 5/10 [00:00<00:00, 13.73it/s, Loss=0.851]
+Epoch 175/10001:  50%|█████     | 5/10 [00:00<00:00, 13.73it/s, Loss=0.855]
+Epoch 175/10001:  50%|█████     | 5/10 [00:00<00:00, 13.73it/s, Loss=0.859]
+Epoch 175/10001: 100%|██████████| 10/10 [00:00<00:00, 15.68it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 176/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 176/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 176/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.857]
+Epoch 176/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.855]
+Epoch 176/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.847]
+Epoch 176/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.856]
+Epoch 176/10001:  40%|████      | 4/10 [00:00<00:00, 10.94it/s, Loss=0.856]
+Epoch 176/10001:  40%|████      | 4/10 [00:00<00:00, 10.94it/s, Loss=0.852]
+Epoch 176/10001:  40%|████      | 4/10 [00:00<00:00, 10.94it/s, Loss=0.844]
+Epoch 176/10001:  40%|████      | 4/10 [00:00<00:00, 10.94it/s, Loss=0.855]
+Epoch 176/10001:  40%|████      | 4/10 [00:00<00:00, 10.94it/s, Loss=0.847]
+Epoch 176/10001:  40%|████      | 4/10 [00:00<00:00, 10.94it/s, Loss=0.855]
+Epoch 176/10001:  90%|█████████ | 9/10 [00:00<00:00, 21.61it/s, Loss=0.855]
+Epoch 176/10001:  90%|█████████ | 9/10 [00:00<00:00, 21.61it/s, Loss=0.85] 
+Epoch 176/10001: 100%|██████████| 10/10 [00:00<00:00, 14.73it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 177/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 177/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.855]
+Epoch 177/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.854]
+Epoch 177/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.855]
+Epoch 177/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.852]
+Epoch 177/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.847]
+Epoch 177/10001:  50%|█████     | 5/10 [00:00<00:00, 12.03it/s, Loss=0.847]
+Epoch 177/10001:  50%|█████     | 5/10 [00:00<00:00, 12.03it/s, Loss=0.847]
+Epoch 177/10001:  50%|█████     | 5/10 [00:00<00:00, 12.03it/s, Loss=0.848]
+Epoch 177/10001:  50%|█████     | 5/10 [00:00<00:00, 12.03it/s, Loss=0.852]
+Epoch 177/10001:  50%|█████     | 5/10 [00:00<00:00, 12.03it/s, Loss=0.856]
+Epoch 177/10001:  50%|█████     | 5/10 [00:00<00:00, 12.03it/s, Loss=0.846]
+Epoch 177/10001: 100%|██████████| 10/10 [00:00<00:00, 22.09it/s, Loss=0.846]
+Epoch 177/10001: 100%|██████████| 10/10 [00:00<00:00, 13.47it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 178/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 178/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 178/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.849]
+Epoch 178/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.857]
+Epoch 178/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.858]
+Epoch 178/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.848]
+Epoch 178/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.844]
+Epoch 178/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.853]
+Epoch 178/10001:  60%|██████    | 6/10 [00:00<00:00, 14.88it/s, Loss=0.853]
+Epoch 178/10001:  60%|██████    | 6/10 [00:00<00:00, 14.88it/s, Loss=0.844]
+Epoch 178/10001:  60%|██████    | 6/10 [00:00<00:00, 14.88it/s, Loss=0.854]
+Epoch 178/10001:  60%|██████    | 6/10 [00:00<00:00, 14.88it/s, Loss=0.852]
+Epoch 178/10001:  60%|██████    | 6/10 [00:00<00:00, 14.88it/s, Loss=0.848]
+Epoch 178/10001: 100%|██████████| 10/10 [00:00<00:00, 14.53it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 179/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 179/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 179/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.848]
+Epoch 179/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.85] 
+Epoch 179/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.851]
+Epoch 179/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.849]
+Epoch 179/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.857]
+Epoch 179/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.857]
+Epoch 179/10001:  60%|██████    | 6/10 [00:00<00:00, 17.03it/s, Loss=0.857]
+Epoch 179/10001:  60%|██████    | 6/10 [00:00<00:00, 17.03it/s, Loss=0.843]
+Epoch 179/10001:  60%|██████    | 6/10 [00:00<00:00, 17.03it/s, Loss=0.857]
+Epoch 179/10001:  60%|██████    | 6/10 [00:00<00:00, 17.03it/s, Loss=0.847]
+Epoch 179/10001:  60%|██████    | 6/10 [00:00<00:00, 17.03it/s, Loss=0.856]
+Epoch 179/10001: 100%|██████████| 10/10 [00:00<00:00, 15.57it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 180/10001:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 180/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.847]
+Epoch 180/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.847]
+Epoch 180/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.852]
+Epoch 180/10001:  50%|█████     | 5/10 [00:00<00:00, 12.10it/s, Loss=0.852]
+Epoch 180/10001:  50%|█████     | 5/10 [00:00<00:00, 12.10it/s, Loss=0.857]
+Epoch 180/10001:  50%|█████     | 5/10 [00:00<00:00, 12.10it/s, Loss=0.849]
+Epoch 180/10001:  50%|█████     | 5/10 [00:00<00:00, 12.10it/s, Loss=0.856]
+Epoch 180/10001:  50%|█████     | 5/10 [00:00<00:00, 12.10it/s, Loss=0.845]
+Epoch 180/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.00it/s, Loss=0.845]
+Epoch 180/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.00it/s, Loss=0.851]
+Epoch 180/10001: 100%|██████████| 10/10 [00:00<00:00, 13.17it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 181/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 181/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 181/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.852]
+Epoch 181/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.851]
+Epoch 181/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.856]
+Epoch 181/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.851]
+Epoch 181/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.851]
+Epoch 181/10001:  50%|█████     | 5/10 [00:00<00:00, 13.58it/s, Loss=0.851]
+Epoch 181/10001:  50%|█████     | 5/10 [00:00<00:00, 13.58it/s, Loss=0.856]
+Epoch 181/10001:  50%|█████     | 5/10 [00:00<00:00, 13.58it/s, Loss=0.849]
+Epoch 181/10001:  50%|█████     | 5/10 [00:00<00:00, 13.58it/s, Loss=0.858]
+Epoch 181/10001:  50%|█████     | 5/10 [00:00<00:00, 13.58it/s, Loss=0.853]
+Epoch 181/10001:  50%|█████     | 5/10 [00:00<00:00, 13.58it/s, Loss=0.858]
+Epoch 181/10001: 100%|██████████| 10/10 [00:00<00:00, 15.67it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 182/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 182/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 182/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.858]
+Epoch 182/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.85] 
+Epoch 182/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.848]
+Epoch 182/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.853]
+Epoch 182/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.858]
+Epoch 182/10001:  50%|█████     | 5/10 [00:00<00:00, 12.38it/s, Loss=0.858]
+Epoch 182/10001:  50%|█████     | 5/10 [00:00<00:00, 12.38it/s, Loss=0.847]
+Epoch 182/10001:  50%|█████     | 5/10 [00:00<00:00, 12.38it/s, Loss=0.851]
+Epoch 182/10001:  50%|█████     | 5/10 [00:00<00:00, 12.38it/s, Loss=0.856]
+Epoch 182/10001:  50%|█████     | 5/10 [00:00<00:00, 12.38it/s, Loss=0.848]
+Epoch 182/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.24it/s, Loss=0.848]
+Epoch 182/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.24it/s, Loss=0.854]
+Epoch 182/10001: 100%|██████████| 10/10 [00:00<00:00, 13.28it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 183/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 183/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 183/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.855]
+Epoch 183/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.854]
+Epoch 183/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.855]
+Epoch 183/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.854]
+Epoch 183/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.847]
+Epoch 183/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.85] 
+Epoch 183/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.851]
+Epoch 183/10001:  70%|███████   | 7/10 [00:00<00:00, 18.95it/s, Loss=0.851]
+Epoch 183/10001:  70%|███████   | 7/10 [00:00<00:00, 18.95it/s, Loss=0.854]
+Epoch 183/10001:  70%|███████   | 7/10 [00:00<00:00, 18.95it/s, Loss=0.856]
+Epoch 183/10001:  70%|███████   | 7/10 [00:00<00:00, 18.95it/s, Loss=0.851]
+Epoch 183/10001: 100%|██████████| 10/10 [00:00<00:00, 15.81it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 184/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 184/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.859]
+Epoch 184/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.859]
+Epoch 184/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.857]
+Epoch 184/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.856]
+Epoch 184/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.852]
+Epoch 184/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.849]
+Epoch 184/10001:  50%|█████     | 5/10 [00:00<00:00, 13.22it/s, Loss=0.849]
+Epoch 184/10001:  50%|█████     | 5/10 [00:00<00:00, 13.22it/s, Loss=0.847]
+Epoch 184/10001:  50%|█████     | 5/10 [00:00<00:00, 13.22it/s, Loss=0.846]
+Epoch 184/10001:  50%|█████     | 5/10 [00:00<00:00, 13.22it/s, Loss=0.852]
+Epoch 184/10001:  50%|█████     | 5/10 [00:00<00:00, 13.22it/s, Loss=0.848]
+Epoch 184/10001:  50%|█████     | 5/10 [00:00<00:00, 13.22it/s, Loss=0.85] 
+Epoch 184/10001: 100%|██████████| 10/10 [00:00<00:00, 22.60it/s, Loss=0.85]
+Epoch 184/10001: 100%|██████████| 10/10 [00:00<00:00, 14.16it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 185/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 185/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 185/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.85]
+Epoch 185/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.852]
+Epoch 185/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.853]
+Epoch 185/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.846]
+Epoch 185/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.848]
+Epoch 185/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.858]
+Epoch 185/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.848]
+Epoch 185/10001:  70%|███████   | 7/10 [00:00<00:00, 15.94it/s, Loss=0.848]
+Epoch 185/10001:  70%|███████   | 7/10 [00:00<00:00, 15.94it/s, Loss=0.849]
+Epoch 185/10001:  70%|███████   | 7/10 [00:00<00:00, 15.94it/s, Loss=0.85] 
+Epoch 185/10001:  70%|███████   | 7/10 [00:00<00:00, 15.94it/s, Loss=0.859]
+Epoch 185/10001: 100%|██████████| 10/10 [00:00<00:00, 13.62it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 186/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 186/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 186/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.845]
+Epoch 186/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.85] 
+Epoch 186/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.855]
+Epoch 186/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.848]
+Epoch 186/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.845]
+Epoch 186/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.848]
+Epoch 186/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.848]
+Epoch 186/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.848]
+Epoch 186/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.857]
+Epoch 186/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.85] 
+Epoch 186/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.846]
+Epoch 186/10001: 100%|██████████| 10/10 [00:00<00:00, 13.19it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 187/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 187/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.86]
+Epoch 187/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.86]
+Epoch 187/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.845]
+Epoch 187/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.855]
+Epoch 187/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.846]
+Epoch 187/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.85] 
+Epoch 187/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.846]
+Epoch 187/10001:  60%|██████    | 6/10 [00:00<00:00, 14.40it/s, Loss=0.846]
+Epoch 187/10001:  60%|██████    | 6/10 [00:00<00:00, 14.40it/s, Loss=0.849]
+Epoch 187/10001:  60%|██████    | 6/10 [00:00<00:00, 14.40it/s, Loss=0.854]
+Epoch 187/10001:  60%|██████    | 6/10 [00:00<00:00, 14.40it/s, Loss=0.856]
+Epoch 187/10001:  60%|██████    | 6/10 [00:00<00:00, 14.40it/s, Loss=0.854]
+Epoch 187/10001: 100%|██████████| 10/10 [00:00<00:00, 13.68it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 188/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 188/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 188/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.85]
+Epoch 188/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.847]
+Epoch 188/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.85] 
+Epoch 188/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.85]
+Epoch 188/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.856]
+Epoch 188/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.853]
+Epoch 188/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.853]
+Epoch 188/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.854]
+Epoch 188/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.854]
+Epoch 188/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.858]
+Epoch 188/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.855]
+Epoch 188/10001: 100%|██████████| 10/10 [00:00<00:00, 15.41it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 189/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 189/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 189/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.854]
+Epoch 189/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.847]
+Epoch 189/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.857]
+Epoch 189/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.843]
+Epoch 189/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.852]
+Epoch 189/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.847]
+Epoch 189/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.848]
+Epoch 189/10001:  70%|███████   | 7/10 [00:00<00:00, 18.22it/s, Loss=0.848]
+Epoch 189/10001:  70%|███████   | 7/10 [00:00<00:00, 18.22it/s, Loss=0.853]
+Epoch 189/10001:  70%|███████   | 7/10 [00:00<00:00, 18.22it/s, Loss=0.854]
+Epoch 189/10001:  70%|███████   | 7/10 [00:00<00:00, 18.22it/s, Loss=0.846]
+Epoch 189/10001: 100%|██████████| 10/10 [00:00<00:00, 15.30it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 190/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 190/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 190/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.845]
+Epoch 190/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.854]
+Epoch 190/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.85] 
+Epoch 190/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.861]
+Epoch 190/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.85] 
+Epoch 190/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.85]
+Epoch 190/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.844]
+Epoch 190/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.852]
+Epoch 190/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.857]
+Epoch 190/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.853]
+Epoch 190/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.40it/s, Loss=0.853]
+Epoch 190/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.40it/s, Loss=0.85] 
+Epoch 190/10001: 100%|██████████| 10/10 [00:00<00:00, 13.37it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 191/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 191/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 191/10001:  10%|█         | 1/10 [00:00<00:04,  2.05it/s, Loss=0.845]
+Epoch 191/10001:  10%|█         | 1/10 [00:00<00:04,  2.05it/s, Loss=0.848]
+Epoch 191/10001:  10%|█         | 1/10 [00:00<00:04,  2.05it/s, Loss=0.849]
+Epoch 191/10001:  10%|█         | 1/10 [00:00<00:04,  2.05it/s, Loss=0.847]
+Epoch 191/10001:  40%|████      | 4/10 [00:00<00:00,  8.37it/s, Loss=0.847]
+Epoch 191/10001:  40%|████      | 4/10 [00:00<00:00,  8.37it/s, Loss=0.854]
+Epoch 191/10001:  40%|████      | 4/10 [00:00<00:00,  8.37it/s, Loss=0.851]
+Epoch 191/10001:  40%|████      | 4/10 [00:00<00:00,  8.37it/s, Loss=0.847]
+Epoch 191/10001:  40%|████      | 4/10 [00:00<00:00,  8.37it/s, Loss=0.844]
+Epoch 191/10001:  80%|████████  | 8/10 [00:00<00:00, 15.73it/s, Loss=0.844]
+Epoch 191/10001:  80%|████████  | 8/10 [00:00<00:00, 15.73it/s, Loss=0.853]
+Epoch 191/10001:  80%|████████  | 8/10 [00:00<00:00, 15.73it/s, Loss=0.848]
+Epoch 191/10001: 100%|██████████| 10/10 [00:00<00:00, 11.43it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 192/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 192/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 192/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.851]
+Epoch 192/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.857]
+Epoch 192/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.849]
+Epoch 192/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.849]
+Epoch 192/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.857]
+Epoch 192/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.85] 
+Epoch 192/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.853]
+Epoch 192/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.851]
+Epoch 192/10001:  80%|████████  | 8/10 [00:00<00:00, 22.57it/s, Loss=0.851]
+Epoch 192/10001:  80%|████████  | 8/10 [00:00<00:00, 22.57it/s, Loss=0.846]
+Epoch 192/10001:  80%|████████  | 8/10 [00:00<00:00, 22.57it/s, Loss=0.844]
+Epoch 192/10001: 100%|██████████| 10/10 [00:00<00:00, 16.41it/s, Loss=0.844]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 193/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 193/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 193/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.848]
+Epoch 193/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.846]
+Epoch 193/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.852]
+Epoch 193/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.852]
+Epoch 193/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.858]
+Epoch 193/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.847]
+Epoch 193/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.85] 
+Epoch 193/10001:  70%|███████   | 7/10 [00:00<00:00, 15.21it/s, Loss=0.85]
+Epoch 193/10001:  70%|███████   | 7/10 [00:00<00:00, 15.21it/s, Loss=0.859]
+Epoch 193/10001:  70%|███████   | 7/10 [00:00<00:00, 15.21it/s, Loss=0.859]
+Epoch 193/10001:  70%|███████   | 7/10 [00:00<00:00, 15.21it/s, Loss=0.867]
+Epoch 193/10001: 100%|██████████| 10/10 [00:00<00:00, 13.04it/s, Loss=0.867]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 194/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 194/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.859]
+Epoch 194/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.859]
+Epoch 194/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.855]
+Epoch 194/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.853]
+Epoch 194/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.857]
+Epoch 194/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.854]
+Epoch 194/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.851]
+Epoch 194/10001:  60%|██████    | 6/10 [00:00<00:00, 14.49it/s, Loss=0.851]
+Epoch 194/10001:  60%|██████    | 6/10 [00:00<00:00, 14.49it/s, Loss=0.852]
+Epoch 194/10001:  60%|██████    | 6/10 [00:00<00:00, 14.49it/s, Loss=0.847]
+Epoch 194/10001:  60%|██████    | 6/10 [00:00<00:00, 14.49it/s, Loss=0.855]
+Epoch 194/10001:  60%|██████    | 6/10 [00:00<00:00, 14.49it/s, Loss=0.852]
+Epoch 194/10001: 100%|██████████| 10/10 [00:00<00:00, 20.76it/s, Loss=0.852]
+Epoch 194/10001: 100%|██████████| 10/10 [00:00<00:00, 13.61it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 195/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 195/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.863]
+Epoch 195/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.863]
+Epoch 195/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.855]
+Epoch 195/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.855]
+Epoch 195/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.852]
+Epoch 195/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.841]
+Epoch 195/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.847]
+Epoch 195/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.847]
+Epoch 195/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.853]
+Epoch 195/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.858]
+Epoch 195/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.849]
+Epoch 195/10001:  60%|██████    | 6/10 [00:00<00:00, 16.16it/s, Loss=0.844]
+Epoch 195/10001: 100%|██████████| 10/10 [00:00<00:00, 15.45it/s, Loss=0.844]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 196/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 196/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 196/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.849]
+Epoch 196/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.847]
+Epoch 196/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.853]
+Epoch 196/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.855]
+Epoch 196/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.854]
+Epoch 196/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.854]
+Epoch 196/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.846]
+Epoch 196/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.855]
+Epoch 196/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.846]
+Epoch 196/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.849]
+Epoch 196/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.51it/s, Loss=0.849]
+Epoch 196/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.51it/s, Loss=0.851]
+Epoch 196/10001: 100%|██████████| 10/10 [00:00<00:00, 13.60it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 197/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 197/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 197/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.85]
+Epoch 197/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.852]
+Epoch 197/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.852]
+Epoch 197/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.851]
+Epoch 197/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.843]
+Epoch 197/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.843]
+Epoch 197/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.858]
+Epoch 197/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.851]
+Epoch 197/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.856]
+Epoch 197/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.854]
+Epoch 197/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.73it/s, Loss=0.854]
+Epoch 197/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.73it/s, Loss=0.849]
+Epoch 197/10001: 100%|██████████| 10/10 [00:00<00:00, 12.14it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 198/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 198/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 198/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.849]
+Epoch 198/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.855]
+Epoch 198/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.849]
+Epoch 198/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.853]
+Epoch 198/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.849]
+Epoch 198/10001:  50%|█████     | 5/10 [00:00<00:00, 13.62it/s, Loss=0.849]
+Epoch 198/10001:  50%|█████     | 5/10 [00:00<00:00, 13.62it/s, Loss=0.847]
+Epoch 198/10001:  50%|█████     | 5/10 [00:00<00:00, 13.62it/s, Loss=0.848]
+Epoch 198/10001:  50%|█████     | 5/10 [00:00<00:00, 13.62it/s, Loss=0.857]
+Epoch 198/10001:  50%|█████     | 5/10 [00:00<00:00, 13.62it/s, Loss=0.841]
+Epoch 198/10001:  50%|█████     | 5/10 [00:00<00:00, 13.62it/s, Loss=0.853]
+Epoch 198/10001: 100%|██████████| 10/10 [00:00<00:00, 14.83it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 199/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 199/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 199/10001:  10%|█         | 1/10 [00:00<00:03,  3.00it/s, Loss=0.848]
+Epoch 199/10001:  10%|█         | 1/10 [00:00<00:03,  3.00it/s, Loss=0.851]
+Epoch 199/10001:  10%|█         | 1/10 [00:00<00:03,  3.00it/s, Loss=0.856]
+Epoch 199/10001:  10%|█         | 1/10 [00:00<00:03,  3.00it/s, Loss=0.847]
+Epoch 199/10001:  10%|█         | 1/10 [00:00<00:03,  3.00it/s, Loss=0.844]
+Epoch 199/10001:  10%|█         | 1/10 [00:00<00:03,  3.00it/s, Loss=0.854]
+Epoch 199/10001:  60%|██████    | 6/10 [00:00<00:00, 17.09it/s, Loss=0.854]
+Epoch 199/10001:  60%|██████    | 6/10 [00:00<00:00, 17.09it/s, Loss=0.846]
+Epoch 199/10001:  60%|██████    | 6/10 [00:00<00:00, 17.09it/s, Loss=0.853]
+Epoch 199/10001:  60%|██████    | 6/10 [00:00<00:00, 17.09it/s, Loss=0.851]
+Epoch 199/10001:  60%|██████    | 6/10 [00:00<00:00, 17.09it/s, Loss=0.851]
+Epoch 199/10001: 100%|██████████| 10/10 [00:00<00:00, 15.83it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 200/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 200/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 200/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.847]
+Epoch 200/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.849]
+Epoch 200/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.854]
+Epoch 200/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.851]
+Epoch 200/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.847]
+Epoch 200/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.847]
+Epoch 200/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.846]
+Epoch 200/10001:  70%|███████   | 7/10 [00:00<00:00, 16.70it/s, Loss=0.846]
+Epoch 200/10001:  70%|███████   | 7/10 [00:00<00:00, 16.70it/s, Loss=0.847]
+Epoch 200/10001:  70%|███████   | 7/10 [00:00<00:00, 16.70it/s, Loss=0.858]
+Epoch 200/10001:  70%|███████   | 7/10 [00:00<00:00, 16.70it/s, Loss=0.862]
+Epoch 200/10001: 100%|██████████| 10/10 [00:00<00:00, 13.47it/s, Loss=0.862]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 201/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 201/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.859]
+Epoch 201/10001:  10%|█         | 1/10 [00:00<00:04,  2.05it/s, Loss=0.859]
+Epoch 201/10001:  10%|█         | 1/10 [00:00<00:04,  2.05it/s, Loss=0.853]
+Epoch 201/10001:  10%|█         | 1/10 [00:00<00:04,  2.05it/s, Loss=0.852]
+Epoch 201/10001:  10%|█         | 1/10 [00:00<00:04,  2.05it/s, Loss=0.857]
+Epoch 201/10001:  10%|█         | 1/10 [00:00<00:04,  2.05it/s, Loss=0.85] 
+Epoch 201/10001:  50%|█████     | 5/10 [00:00<00:00, 10.48it/s, Loss=0.85]
+Epoch 201/10001:  50%|█████     | 5/10 [00:00<00:00, 10.48it/s, Loss=0.857]
+Epoch 201/10001:  50%|█████     | 5/10 [00:00<00:00, 10.48it/s, Loss=0.844]
+Epoch 201/10001:  50%|█████     | 5/10 [00:00<00:00, 10.48it/s, Loss=0.848]
+Epoch 201/10001:  50%|█████     | 5/10 [00:00<00:00, 10.48it/s, Loss=0.853]
+Epoch 201/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.04it/s, Loss=0.853]
+Epoch 201/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.04it/s, Loss=0.851]
+Epoch 201/10001: 100%|██████████| 10/10 [00:00<00:00, 11.47it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 202/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 202/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 202/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.852]
+Epoch 202/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.844]
+Epoch 202/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.854]
+Epoch 202/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.855]
+Epoch 202/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.851]
+Epoch 202/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.855]
+Epoch 202/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.855]
+Epoch 202/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.855]
+Epoch 202/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.845]
+Epoch 202/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.848]
+Epoch 202/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.854]
+Epoch 202/10001: 100%|██████████| 10/10 [00:00<00:00, 20.10it/s, Loss=0.854]
+Epoch 202/10001: 100%|██████████| 10/10 [00:00<00:00, 13.24it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 203/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 203/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 203/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.85]
+Epoch 203/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.847]
+Epoch 203/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.853]
+Epoch 203/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.844]
+Epoch 203/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.855]
+Epoch 203/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.86] 
+Epoch 203/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.86]
+Epoch 203/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.854]
+Epoch 203/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.851]
+Epoch 203/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.848]
+Epoch 203/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.852]
+Epoch 203/10001: 100%|██████████| 10/10 [00:00<00:00, 22.15it/s, Loss=0.852]
+Epoch 203/10001: 100%|██████████| 10/10 [00:00<00:00, 14.68it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 204/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 204/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 204/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.852]
+Epoch 204/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.851]
+Epoch 204/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.85] 
+Epoch 204/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.838]
+Epoch 204/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.838]
+Epoch 204/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.845]
+Epoch 204/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.855]
+Epoch 204/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.85] 
+Epoch 204/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.857]
+Epoch 204/10001:  80%|████████  | 8/10 [00:00<00:00, 16.59it/s, Loss=0.857]
+Epoch 204/10001:  80%|████████  | 8/10 [00:00<00:00, 16.59it/s, Loss=0.842]
+Epoch 204/10001:  80%|████████  | 8/10 [00:00<00:00, 16.59it/s, Loss=0.857]
+Epoch 204/10001: 100%|██████████| 10/10 [00:00<00:00, 12.34it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 205/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 205/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 205/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.854]
+Epoch 205/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.855]
+Epoch 205/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.844]
+Epoch 205/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.848]
+Epoch 205/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.858]
+Epoch 205/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.845]
+Epoch 205/10001:  60%|██████    | 6/10 [00:00<00:00, 17.00it/s, Loss=0.845]
+Epoch 205/10001:  60%|██████    | 6/10 [00:00<00:00, 17.00it/s, Loss=0.85] 
+Epoch 205/10001:  60%|██████    | 6/10 [00:00<00:00, 17.00it/s, Loss=0.853]
+Epoch 205/10001:  60%|██████    | 6/10 [00:00<00:00, 17.00it/s, Loss=0.851]
+Epoch 205/10001:  60%|██████    | 6/10 [00:00<00:00, 17.00it/s, Loss=0.846]
+Epoch 205/10001: 100%|██████████| 10/10 [00:00<00:00, 15.95it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 206/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 206/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 206/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.85]
+Epoch 206/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.848]
+Epoch 206/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.851]
+Epoch 206/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.847]
+Epoch 206/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.852]
+Epoch 206/10001:  50%|█████     | 5/10 [00:00<00:00, 12.60it/s, Loss=0.852]
+Epoch 206/10001:  50%|█████     | 5/10 [00:00<00:00, 12.60it/s, Loss=0.852]
+Epoch 206/10001:  50%|█████     | 5/10 [00:00<00:00, 12.60it/s, Loss=0.847]
+Epoch 206/10001:  50%|█████     | 5/10 [00:00<00:00, 12.60it/s, Loss=0.858]
+Epoch 206/10001:  50%|█████     | 5/10 [00:00<00:00, 12.60it/s, Loss=0.853]
+Epoch 206/10001:  50%|█████     | 5/10 [00:00<00:00, 12.60it/s, Loss=0.85] 
+Epoch 206/10001: 100%|██████████| 10/10 [00:00<00:00, 21.89it/s, Loss=0.85]
+Epoch 206/10001: 100%|██████████| 10/10 [00:00<00:00, 14.16it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 207/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 207/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 207/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.85]
+Epoch 207/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.85]
+Epoch 207/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.85]
+Epoch 207/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.848]
+Epoch 207/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.858]
+Epoch 207/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.849]
+Epoch 207/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.854]
+Epoch 207/10001:  70%|███████   | 7/10 [00:00<00:00, 19.76it/s, Loss=0.854]
+Epoch 207/10001:  70%|███████   | 7/10 [00:00<00:00, 19.76it/s, Loss=0.847]
+Epoch 207/10001:  70%|███████   | 7/10 [00:00<00:00, 19.76it/s, Loss=0.848]
+Epoch 207/10001:  70%|███████   | 7/10 [00:00<00:00, 19.76it/s, Loss=0.851]
+Epoch 207/10001: 100%|██████████| 10/10 [00:00<00:00, 17.27it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 208/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 208/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 208/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.848]
+Epoch 208/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.855]
+Epoch 208/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.849]
+Epoch 208/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.847]
+Epoch 208/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.85] 
+Epoch 208/10001:  50%|█████     | 5/10 [00:00<00:00, 12.78it/s, Loss=0.85]
+Epoch 208/10001:  50%|█████     | 5/10 [00:00<00:00, 12.78it/s, Loss=0.855]
+Epoch 208/10001:  50%|█████     | 5/10 [00:00<00:00, 12.78it/s, Loss=0.85] 
+Epoch 208/10001:  50%|█████     | 5/10 [00:00<00:00, 12.78it/s, Loss=0.855]
+Epoch 208/10001:  50%|█████     | 5/10 [00:00<00:00, 12.78it/s, Loss=0.845]
+Epoch 208/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.73it/s, Loss=0.845]
+Epoch 208/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.73it/s, Loss=0.843]
+Epoch 208/10001: 100%|██████████| 10/10 [00:00<00:00, 14.15it/s, Loss=0.843]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 209/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 209/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 209/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.854]
+Epoch 209/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.848]
+Epoch 209/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.847]
+Epoch 209/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.849]
+Epoch 209/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.847]
+Epoch 209/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.853]
+Epoch 209/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.854]
+Epoch 209/10001:  70%|███████   | 7/10 [00:00<00:00, 19.47it/s, Loss=0.854]
+Epoch 209/10001:  70%|███████   | 7/10 [00:00<00:00, 19.47it/s, Loss=0.855]
+Epoch 209/10001:  70%|███████   | 7/10 [00:00<00:00, 19.47it/s, Loss=0.853]
+Epoch 209/10001:  70%|███████   | 7/10 [00:00<00:00, 19.47it/s, Loss=0.851]
+Epoch 209/10001: 100%|██████████| 10/10 [00:00<00:00, 16.70it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 210/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 210/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 210/10001:  10%|█         | 1/10 [00:00<00:02,  3.24it/s, Loss=0.852]
+Epoch 210/10001:  10%|█         | 1/10 [00:00<00:02,  3.24it/s, Loss=0.848]
+Epoch 210/10001:  10%|█         | 1/10 [00:00<00:02,  3.24it/s, Loss=0.845]
+Epoch 210/10001:  10%|█         | 1/10 [00:00<00:02,  3.24it/s, Loss=0.854]
+Epoch 210/10001:  10%|█         | 1/10 [00:00<00:02,  3.24it/s, Loss=0.85] 
+Epoch 210/10001:  10%|█         | 1/10 [00:00<00:02,  3.24it/s, Loss=0.855]
+Epoch 210/10001:  10%|█         | 1/10 [00:00<00:02,  3.24it/s, Loss=0.849]
+Epoch 210/10001:  70%|███████   | 7/10 [00:00<00:00, 21.14it/s, Loss=0.849]
+Epoch 210/10001:  70%|███████   | 7/10 [00:00<00:00, 21.14it/s, Loss=0.849]
+Epoch 210/10001:  70%|███████   | 7/10 [00:00<00:00, 21.14it/s, Loss=0.851]
+Epoch 210/10001:  70%|███████   | 7/10 [00:00<00:00, 21.14it/s, Loss=0.856]
+Epoch 210/10001: 100%|██████████| 10/10 [00:00<00:00, 17.31it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 211/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 211/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 211/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.848]
+Epoch 211/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.847]
+Epoch 211/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.848]
+Epoch 211/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.848]
+Epoch 211/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.855]
+Epoch 211/10001:  50%|█████     | 5/10 [00:00<00:00, 12.14it/s, Loss=0.855]
+Epoch 211/10001:  50%|█████     | 5/10 [00:00<00:00, 12.14it/s, Loss=0.848]
+Epoch 211/10001:  50%|█████     | 5/10 [00:00<00:00, 12.14it/s, Loss=0.849]
+Epoch 211/10001:  50%|█████     | 5/10 [00:00<00:00, 12.14it/s, Loss=0.848]
+Epoch 211/10001:  50%|█████     | 5/10 [00:00<00:00, 12.14it/s, Loss=0.851]
+Epoch 211/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.46it/s, Loss=0.851]
+Epoch 211/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.46it/s, Loss=0.848]
+Epoch 211/10001: 100%|██████████| 10/10 [00:00<00:00, 12.88it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 212/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 212/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 212/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.853]
+Epoch 212/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.848]
+Epoch 212/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.854]
+Epoch 212/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.851]
+Epoch 212/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.857]
+Epoch 212/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.841]
+Epoch 212/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.841]
+Epoch 212/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.852]
+Epoch 212/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.857]
+Epoch 212/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.85] 
+Epoch 212/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.853]
+Epoch 212/10001: 100%|██████████| 10/10 [00:00<00:00, 13.33it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 213/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 213/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 213/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.854]
+Epoch 213/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.845]
+Epoch 213/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.846]
+Epoch 213/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.852]
+Epoch 213/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.843]
+Epoch 213/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.843]
+Epoch 213/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.851]
+Epoch 213/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.853]
+Epoch 213/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.846]
+Epoch 213/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.853]
+Epoch 213/10001:  50%|█████     | 5/10 [00:00<00:00, 12.56it/s, Loss=0.849]
+Epoch 213/10001: 100%|██████████| 10/10 [00:00<00:00, 14.61it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 214/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 214/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 214/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.855]
+Epoch 214/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.856]
+Epoch 214/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.851]
+Epoch 214/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.842]
+Epoch 214/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.857]
+Epoch 214/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.857]
+Epoch 214/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.846]
+Epoch 214/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.852]
+Epoch 214/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.856]
+Epoch 214/10001:  50%|█████     | 5/10 [00:00<00:00, 13.33it/s, Loss=0.855]
+Epoch 214/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.08it/s, Loss=0.855]
+Epoch 214/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.08it/s, Loss=0.848]
+Epoch 214/10001: 100%|██████████| 10/10 [00:00<00:00, 14.23it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 215/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 215/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 215/10001:  10%|█         | 1/10 [00:00<00:02,  3.12it/s, Loss=0.855]
+Epoch 215/10001:  10%|█         | 1/10 [00:00<00:02,  3.12it/s, Loss=0.852]
+Epoch 215/10001:  10%|█         | 1/10 [00:00<00:02,  3.12it/s, Loss=0.849]
+Epoch 215/10001:  10%|█         | 1/10 [00:00<00:02,  3.12it/s, Loss=0.848]
+Epoch 215/10001:  10%|█         | 1/10 [00:00<00:02,  3.12it/s, Loss=0.853]
+Epoch 215/10001:  10%|█         | 1/10 [00:00<00:02,  3.12it/s, Loss=0.854]
+Epoch 215/10001:  10%|█         | 1/10 [00:00<00:02,  3.12it/s, Loss=0.86] 
+Epoch 215/10001:  70%|███████   | 7/10 [00:00<00:00, 19.35it/s, Loss=0.86]
+Epoch 215/10001:  70%|███████   | 7/10 [00:00<00:00, 19.35it/s, Loss=0.851]
+Epoch 215/10001:  70%|███████   | 7/10 [00:00<00:00, 19.35it/s, Loss=0.847]
+Epoch 215/10001:  70%|███████   | 7/10 [00:00<00:00, 19.35it/s, Loss=0.851]
+Epoch 215/10001: 100%|██████████| 10/10 [00:00<00:00, 16.60it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 216/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 216/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 216/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.848]
+Epoch 216/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.851]
+Epoch 216/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.86] 
+Epoch 216/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.848]
+Epoch 216/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.853]
+Epoch 216/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.852]
+Epoch 216/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.846]
+Epoch 216/10001:  70%|███████   | 7/10 [00:00<00:00, 19.39it/s, Loss=0.846]
+Epoch 216/10001:  70%|███████   | 7/10 [00:00<00:00, 19.39it/s, Loss=0.849]
+Epoch 216/10001:  70%|███████   | 7/10 [00:00<00:00, 19.39it/s, Loss=0.857]
+Epoch 216/10001:  70%|███████   | 7/10 [00:00<00:00, 19.39it/s, Loss=0.849]
+Epoch 216/10001: 100%|██████████| 10/10 [00:00<00:00, 15.98it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 217/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 217/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 217/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.849]
+Epoch 217/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.853]
+Epoch 217/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.853]
+Epoch 217/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.849]
+Epoch 217/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.848]
+Epoch 217/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.847]
+Epoch 217/10001:  60%|██████    | 6/10 [00:00<00:00, 14.05it/s, Loss=0.847]
+Epoch 217/10001:  60%|██████    | 6/10 [00:00<00:00, 14.05it/s, Loss=0.853]
+Epoch 217/10001:  60%|██████    | 6/10 [00:00<00:00, 14.05it/s, Loss=0.854]
+Epoch 217/10001:  60%|██████    | 6/10 [00:00<00:00, 14.05it/s, Loss=0.854]
+Epoch 217/10001:  60%|██████    | 6/10 [00:00<00:00, 14.05it/s, Loss=0.853]
+Epoch 217/10001: 100%|██████████| 10/10 [00:00<00:00, 13.96it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 218/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 218/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 218/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.85]
+Epoch 218/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.856]
+Epoch 218/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.85] 
+Epoch 218/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.857]
+Epoch 218/10001:  40%|████      | 4/10 [00:00<00:00,  8.86it/s, Loss=0.857]
+Epoch 218/10001:  40%|████      | 4/10 [00:00<00:00,  8.86it/s, Loss=0.845]
+Epoch 218/10001:  40%|████      | 4/10 [00:00<00:00,  8.86it/s, Loss=0.851]
+Epoch 218/10001:  40%|████      | 4/10 [00:00<00:00,  8.86it/s, Loss=0.842]
+Epoch 218/10001:  40%|████      | 4/10 [00:00<00:00,  8.86it/s, Loss=0.851]
+Epoch 218/10001:  80%|████████  | 8/10 [00:00<00:00, 16.34it/s, Loss=0.851]
+Epoch 218/10001:  80%|████████  | 8/10 [00:00<00:00, 16.34it/s, Loss=0.86] 
+Epoch 218/10001:  80%|████████  | 8/10 [00:00<00:00, 16.34it/s, Loss=0.853]
+Epoch 218/10001: 100%|██████████| 10/10 [00:00<00:00, 11.98it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 219/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 219/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 219/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.847]
+Epoch 219/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.849]
+Epoch 219/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.851]
+Epoch 219/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.847]
+Epoch 219/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.856]
+Epoch 219/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.852]
+Epoch 219/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.855]
+Epoch 219/10001:  70%|███████   | 7/10 [00:00<00:00, 15.54it/s, Loss=0.855]
+Epoch 219/10001:  70%|███████   | 7/10 [00:00<00:00, 15.54it/s, Loss=0.855]
+Epoch 219/10001:  70%|███████   | 7/10 [00:00<00:00, 15.54it/s, Loss=0.85] 
+Epoch 219/10001:  70%|███████   | 7/10 [00:00<00:00, 15.54it/s, Loss=0.85]
+Epoch 219/10001: 100%|██████████| 10/10 [00:00<00:00, 13.64it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 220/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 220/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 220/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.85]
+Epoch 220/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.849]
+Epoch 220/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.853]
+Epoch 220/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.859]
+Epoch 220/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.858]
+Epoch 220/10001:  50%|█████     | 5/10 [00:00<00:00, 13.32it/s, Loss=0.858]
+Epoch 220/10001:  50%|█████     | 5/10 [00:00<00:00, 13.32it/s, Loss=0.853]
+Epoch 220/10001:  50%|█████     | 5/10 [00:00<00:00, 13.32it/s, Loss=0.847]
+Epoch 220/10001:  50%|█████     | 5/10 [00:00<00:00, 13.32it/s, Loss=0.85] 
+Epoch 220/10001:  50%|█████     | 5/10 [00:00<00:00, 13.32it/s, Loss=0.852]
+Epoch 220/10001:  50%|█████     | 5/10 [00:00<00:00, 13.32it/s, Loss=0.856]
+Epoch 220/10001: 100%|██████████| 10/10 [00:00<00:00, 14.80it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 221/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 221/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 221/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.857]
+Epoch 221/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.855]
+Epoch 221/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.846]
+Epoch 221/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.853]
+Epoch 221/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.857]
+Epoch 221/10001:  50%|█████     | 5/10 [00:00<00:00, 11.80it/s, Loss=0.857]
+Epoch 221/10001:  50%|█████     | 5/10 [00:00<00:00, 11.80it/s, Loss=0.848]
+Epoch 221/10001:  50%|█████     | 5/10 [00:00<00:00, 11.80it/s, Loss=0.845]
+Epoch 221/10001:  50%|█████     | 5/10 [00:00<00:00, 11.80it/s, Loss=0.858]
+Epoch 221/10001:  50%|█████     | 5/10 [00:00<00:00, 11.80it/s, Loss=0.849]
+Epoch 221/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.67it/s, Loss=0.849]
+Epoch 221/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.67it/s, Loss=0.849]
+Epoch 221/10001: 100%|██████████| 10/10 [00:00<00:00, 12.81it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 222/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 222/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 222/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.845]
+Epoch 222/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.845]
+Epoch 222/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.858]
+Epoch 222/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.848]
+Epoch 222/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.844]
+Epoch 222/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.855]
+Epoch 222/10001:  60%|██████    | 6/10 [00:00<00:00, 13.86it/s, Loss=0.855]
+Epoch 222/10001:  60%|██████    | 6/10 [00:00<00:00, 13.86it/s, Loss=0.857]
+Epoch 222/10001:  60%|██████    | 6/10 [00:00<00:00, 13.86it/s, Loss=0.849]
+Epoch 222/10001:  60%|██████    | 6/10 [00:00<00:00, 13.86it/s, Loss=0.844]
+Epoch 222/10001:  60%|██████    | 6/10 [00:00<00:00, 13.86it/s, Loss=0.847]
+Epoch 222/10001: 100%|██████████| 10/10 [00:00<00:00, 13.86it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 223/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 223/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 223/10001:  10%|█         | 1/10 [00:00<00:02,  3.25it/s, Loss=0.855]
+Epoch 223/10001:  10%|█         | 1/10 [00:00<00:02,  3.25it/s, Loss=0.85] 
+Epoch 223/10001:  10%|█         | 1/10 [00:00<00:02,  3.25it/s, Loss=0.846]
+Epoch 223/10001:  10%|█         | 1/10 [00:00<00:02,  3.25it/s, Loss=0.843]
+Epoch 223/10001:  10%|█         | 1/10 [00:00<00:02,  3.25it/s, Loss=0.854]
+Epoch 223/10001:  50%|█████     | 5/10 [00:00<00:00, 13.74it/s, Loss=0.854]
+Epoch 223/10001:  50%|█████     | 5/10 [00:00<00:00, 13.74it/s, Loss=0.848]
+Epoch 223/10001:  50%|█████     | 5/10 [00:00<00:00, 13.74it/s, Loss=0.857]
+Epoch 223/10001:  50%|█████     | 5/10 [00:00<00:00, 13.74it/s, Loss=0.849]
+Epoch 223/10001:  50%|█████     | 5/10 [00:00<00:00, 13.74it/s, Loss=0.844]
+Epoch 223/10001:  50%|█████     | 5/10 [00:00<00:00, 13.74it/s, Loss=0.848]
+Epoch 223/10001: 100%|██████████| 10/10 [00:00<00:00, 23.80it/s, Loss=0.848]
+Epoch 223/10001: 100%|██████████| 10/10 [00:00<00:00, 15.33it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 224/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 224/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 224/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.854]
+Epoch 224/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.851]
+Epoch 224/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.854]
+Epoch 224/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.856]
+Epoch 224/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.852]
+Epoch 224/10001:  50%|█████     | 5/10 [00:00<00:00, 12.96it/s, Loss=0.852]
+Epoch 224/10001:  50%|█████     | 5/10 [00:00<00:00, 12.96it/s, Loss=0.859]
+Epoch 224/10001:  50%|█████     | 5/10 [00:00<00:00, 12.96it/s, Loss=0.845]
+Epoch 224/10001:  50%|█████     | 5/10 [00:00<00:00, 12.96it/s, Loss=0.864]
+Epoch 224/10001:  50%|█████     | 5/10 [00:00<00:00, 12.96it/s, Loss=0.852]
+Epoch 224/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.03it/s, Loss=0.852]
+Epoch 224/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.03it/s, Loss=0.854]
+Epoch 224/10001: 100%|██████████| 10/10 [00:00<00:00, 14.12it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 225/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 225/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 225/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.848]
+Epoch 225/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.858]
+Epoch 225/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.847]
+Epoch 225/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.859]
+Epoch 225/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.847]
+Epoch 225/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.849]
+Epoch 225/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.859]
+Epoch 225/10001:  10%|█         | 1/10 [00:00<00:03,  2.48it/s, Loss=0.855]
+Epoch 225/10001:  80%|████████  | 8/10 [00:00<00:00, 19.43it/s, Loss=0.855]
+Epoch 225/10001:  80%|████████  | 8/10 [00:00<00:00, 19.43it/s, Loss=0.851]
+Epoch 225/10001:  80%|████████  | 8/10 [00:00<00:00, 19.43it/s, Loss=0.849]
+Epoch 225/10001: 100%|██████████| 10/10 [00:00<00:00, 14.73it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 226/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 226/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 226/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.848]
+Epoch 226/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.849]
+Epoch 226/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.854]
+Epoch 226/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.854]
+Epoch 226/10001:  40%|████      | 4/10 [00:00<00:00,  9.45it/s, Loss=0.854]
+Epoch 226/10001:  40%|████      | 4/10 [00:00<00:00,  9.45it/s, Loss=0.853]
+Epoch 226/10001:  40%|████      | 4/10 [00:00<00:00,  9.45it/s, Loss=0.857]
+Epoch 226/10001:  40%|████      | 4/10 [00:00<00:00,  9.45it/s, Loss=0.848]
+Epoch 226/10001:  40%|████      | 4/10 [00:00<00:00,  9.45it/s, Loss=0.853]
+Epoch 226/10001:  80%|████████  | 8/10 [00:00<00:00, 17.05it/s, Loss=0.853]
+Epoch 226/10001:  80%|████████  | 8/10 [00:00<00:00, 17.05it/s, Loss=0.857]
+Epoch 226/10001:  80%|████████  | 8/10 [00:00<00:00, 17.05it/s, Loss=0.854]
+Epoch 226/10001: 100%|██████████| 10/10 [00:00<00:00, 12.80it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 227/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 227/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 227/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.856]
+Epoch 227/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.847]
+Epoch 227/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.852]
+Epoch 227/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.856]
+Epoch 227/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.849]
+Epoch 227/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.855]
+Epoch 227/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.853]
+Epoch 227/10001:  70%|███████   | 7/10 [00:00<00:00, 18.96it/s, Loss=0.853]
+Epoch 227/10001:  70%|███████   | 7/10 [00:00<00:00, 18.96it/s, Loss=0.854]
+Epoch 227/10001:  70%|███████   | 7/10 [00:00<00:00, 18.96it/s, Loss=0.851]
+Epoch 227/10001:  70%|███████   | 7/10 [00:00<00:00, 18.96it/s, Loss=0.853]
+Epoch 227/10001: 100%|██████████| 10/10 [00:00<00:00, 14.04it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 228/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 228/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 228/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.854]
+Epoch 228/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.851]
+Epoch 228/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.851]
+Epoch 228/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.85] 
+Epoch 228/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.848]
+Epoch 228/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.85] 
+Epoch 228/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.85]
+Epoch 228/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.848]
+Epoch 228/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.853]
+Epoch 228/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.39it/s, Loss=0.853]
+Epoch 228/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.39it/s, Loss=0.854]
+Epoch 228/10001: 100%|██████████| 10/10 [00:00<00:00, 13.97it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 229/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 229/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 229/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.853]
+Epoch 229/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.849]
+Epoch 229/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.852]
+Epoch 229/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.855]
+Epoch 229/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.857]
+Epoch 229/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.854]
+Epoch 229/10001:  60%|██████    | 6/10 [00:00<00:00, 16.20it/s, Loss=0.854]
+Epoch 229/10001:  60%|██████    | 6/10 [00:00<00:00, 16.20it/s, Loss=0.853]
+Epoch 229/10001:  60%|██████    | 6/10 [00:00<00:00, 16.20it/s, Loss=0.857]
+Epoch 229/10001:  60%|██████    | 6/10 [00:00<00:00, 16.20it/s, Loss=0.848]
+Epoch 229/10001:  60%|██████    | 6/10 [00:00<00:00, 16.20it/s, Loss=0.858]
+Epoch 229/10001: 100%|██████████| 10/10 [00:00<00:00, 14.98it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 230/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 230/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 230/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.85]
+Epoch 230/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.859]
+Epoch 230/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.845]
+Epoch 230/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.855]
+Epoch 230/10001:  10%|█         | 1/10 [00:00<00:02,  3.02it/s, Loss=0.854]
+Epoch 230/10001:  50%|█████     | 5/10 [00:00<00:00, 13.59it/s, Loss=0.854]
+Epoch 230/10001:  50%|█████     | 5/10 [00:00<00:00, 13.59it/s, Loss=0.855]
+Epoch 230/10001:  50%|█████     | 5/10 [00:00<00:00, 13.59it/s, Loss=0.855]
+Epoch 230/10001:  50%|█████     | 5/10 [00:00<00:00, 13.59it/s, Loss=0.862]
+Epoch 230/10001:  50%|█████     | 5/10 [00:00<00:00, 13.59it/s, Loss=0.848]
+Epoch 230/10001:  50%|█████     | 5/10 [00:00<00:00, 13.59it/s, Loss=0.852]
+Epoch 230/10001: 100%|██████████| 10/10 [00:00<00:00, 15.59it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 231/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 231/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.859]
+Epoch 231/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.859]
+Epoch 231/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.858]
+Epoch 231/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.859]
+Epoch 231/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.85] 
+Epoch 231/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.845]
+Epoch 231/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.851]
+Epoch 231/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.86] 
+Epoch 231/10001:  70%|███████   | 7/10 [00:00<00:00, 19.00it/s, Loss=0.86]
+Epoch 231/10001:  70%|███████   | 7/10 [00:00<00:00, 19.00it/s, Loss=0.852]
+Epoch 231/10001:  70%|███████   | 7/10 [00:00<00:00, 19.00it/s, Loss=0.85] 
+Epoch 231/10001:  70%|███████   | 7/10 [00:00<00:00, 19.00it/s, Loss=0.853]
+Epoch 231/10001: 100%|██████████| 10/10 [00:00<00:00, 16.44it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 232/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 232/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 232/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.849]
+Epoch 232/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.857]
+Epoch 232/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.842]
+Epoch 232/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.862]
+Epoch 232/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.845]
+Epoch 232/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.855]
+Epoch 232/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.852]
+Epoch 232/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.84] 
+Epoch 232/10001:  80%|████████  | 8/10 [00:00<00:00, 20.62it/s, Loss=0.84]
+Epoch 232/10001:  80%|████████  | 8/10 [00:00<00:00, 20.62it/s, Loss=0.852]
+Epoch 232/10001:  80%|████████  | 8/10 [00:00<00:00, 20.62it/s, Loss=0.853]
+Epoch 232/10001: 100%|██████████| 10/10 [00:00<00:00, 15.69it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 233/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 233/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 233/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.847]
+Epoch 233/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.849]
+Epoch 233/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.854]
+Epoch 233/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.847]
+Epoch 233/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 233/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.85] 
+Epoch 233/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.85]
+Epoch 233/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.849]
+Epoch 233/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.846]
+Epoch 233/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.846]
+Epoch 233/10001:  60%|██████    | 6/10 [00:00<00:00, 13.74it/s, Loss=0.853]
+Epoch 233/10001: 100%|██████████| 10/10 [00:00<00:00, 20.01it/s, Loss=0.853]
+Epoch 233/10001: 100%|██████████| 10/10 [00:00<00:00, 12.69it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 234/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 234/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 234/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.85]
+Epoch 234/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.856]
+Epoch 234/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.849]
+Epoch 234/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.847]
+Epoch 234/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.843]
+Epoch 234/10001:  50%|█████     | 5/10 [00:00<00:00, 10.88it/s, Loss=0.843]
+Epoch 234/10001:  50%|█████     | 5/10 [00:00<00:00, 10.88it/s, Loss=0.846]
+Epoch 234/10001:  50%|█████     | 5/10 [00:00<00:00, 10.88it/s, Loss=0.857]
+Epoch 234/10001:  50%|█████     | 5/10 [00:00<00:00, 10.88it/s, Loss=0.851]
+Epoch 234/10001:  50%|█████     | 5/10 [00:00<00:00, 10.88it/s, Loss=0.847]
+Epoch 234/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.44it/s, Loss=0.847]
+Epoch 234/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.44it/s, Loss=0.857]
+Epoch 234/10001: 100%|██████████| 10/10 [00:00<00:00, 12.11it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 235/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 235/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 235/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.852]
+Epoch 235/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.846]
+Epoch 235/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.85] 
+Epoch 235/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.858]
+Epoch 235/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.852]
+Epoch 235/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.852]
+Epoch 235/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.857]
+Epoch 235/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.854]
+Epoch 235/10001:  80%|████████  | 8/10 [00:00<00:00, 22.19it/s, Loss=0.854]
+Epoch 235/10001:  80%|████████  | 8/10 [00:00<00:00, 22.19it/s, Loss=0.845]
+Epoch 235/10001:  80%|████████  | 8/10 [00:00<00:00, 22.19it/s, Loss=0.855]
+Epoch 235/10001: 100%|██████████| 10/10 [00:00<00:00, 15.87it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 236/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 236/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 236/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.852]
+Epoch 236/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.847]
+Epoch 236/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.856]
+Epoch 236/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.863]
+Epoch 236/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.85] 
+Epoch 236/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.846]
+Epoch 236/10001:  60%|██████    | 6/10 [00:00<00:00, 14.36it/s, Loss=0.846]
+Epoch 236/10001:  60%|██████    | 6/10 [00:00<00:00, 14.36it/s, Loss=0.853]
+Epoch 236/10001:  60%|██████    | 6/10 [00:00<00:00, 14.36it/s, Loss=0.844]
+Epoch 236/10001:  60%|██████    | 6/10 [00:00<00:00, 14.36it/s, Loss=0.852]
+Epoch 236/10001:  60%|██████    | 6/10 [00:00<00:00, 14.36it/s, Loss=0.852]
+Epoch 236/10001: 100%|██████████| 10/10 [00:00<00:00, 14.17it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 237/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 237/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 237/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.848]
+Epoch 237/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.851]
+Epoch 237/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.849]
+Epoch 237/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.853]
+Epoch 237/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.856]
+Epoch 237/10001:  50%|█████     | 5/10 [00:00<00:00, 13.84it/s, Loss=0.856]
+Epoch 237/10001:  50%|█████     | 5/10 [00:00<00:00, 13.84it/s, Loss=0.845]
+Epoch 237/10001:  50%|█████     | 5/10 [00:00<00:00, 13.84it/s, Loss=0.843]
+Epoch 237/10001:  50%|█████     | 5/10 [00:00<00:00, 13.84it/s, Loss=0.851]
+Epoch 237/10001:  50%|█████     | 5/10 [00:00<00:00, 13.84it/s, Loss=0.85] 
+Epoch 237/10001:  50%|█████     | 5/10 [00:00<00:00, 13.84it/s, Loss=0.854]
+Epoch 237/10001: 100%|██████████| 10/10 [00:00<00:00, 24.30it/s, Loss=0.854]
+Epoch 237/10001: 100%|██████████| 10/10 [00:00<00:00, 15.40it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 238/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 238/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 238/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.856]
+Epoch 238/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.838]
+Epoch 238/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.852]
+Epoch 238/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.852]
+Epoch 238/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.845]
+Epoch 238/10001:  50%|█████     | 5/10 [00:00<00:00, 13.78it/s, Loss=0.845]
+Epoch 238/10001:  50%|█████     | 5/10 [00:00<00:00, 13.78it/s, Loss=0.856]
+Epoch 238/10001:  50%|█████     | 5/10 [00:00<00:00, 13.78it/s, Loss=0.853]
+Epoch 238/10001:  50%|█████     | 5/10 [00:00<00:00, 13.78it/s, Loss=0.855]
+Epoch 238/10001:  50%|█████     | 5/10 [00:00<00:00, 13.78it/s, Loss=0.849]
+Epoch 238/10001:  50%|█████     | 5/10 [00:00<00:00, 13.78it/s, Loss=0.854]
+Epoch 238/10001: 100%|██████████| 10/10 [00:00<00:00, 14.91it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 239/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 239/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 239/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.848]
+Epoch 239/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.857]
+Epoch 239/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.85] 
+Epoch 239/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.847]
+Epoch 239/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.851]
+Epoch 239/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.857]
+Epoch 239/10001:  60%|██████    | 6/10 [00:00<00:00, 13.13it/s, Loss=0.857]
+Epoch 239/10001:  60%|██████    | 6/10 [00:00<00:00, 13.13it/s, Loss=0.85] 
+Epoch 239/10001:  60%|██████    | 6/10 [00:00<00:00, 13.13it/s, Loss=0.847]
+Epoch 239/10001:  60%|██████    | 6/10 [00:00<00:00, 13.13it/s, Loss=0.856]
+Epoch 239/10001:  60%|██████    | 6/10 [00:00<00:00, 13.13it/s, Loss=0.848]
+Epoch 239/10001: 100%|██████████| 10/10 [00:00<00:00, 18.66it/s, Loss=0.848]
+Epoch 239/10001: 100%|██████████| 10/10 [00:00<00:00, 11.91it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 240/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 240/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 240/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 240/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 240/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.857]
+Epoch 240/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.847]
+Epoch 240/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.865]
+Epoch 240/10001:  50%|█████     | 5/10 [00:00<00:00, 11.23it/s, Loss=0.865]
+Epoch 240/10001:  50%|█████     | 5/10 [00:00<00:00, 11.23it/s, Loss=0.849]
+Epoch 240/10001:  50%|█████     | 5/10 [00:00<00:00, 11.23it/s, Loss=0.854]
+Epoch 240/10001:  50%|█████     | 5/10 [00:00<00:00, 11.23it/s, Loss=0.847]
+Epoch 240/10001:  50%|█████     | 5/10 [00:00<00:00, 11.23it/s, Loss=0.852]
+Epoch 240/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.71it/s, Loss=0.852]
+Epoch 240/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.71it/s, Loss=0.858]
+Epoch 240/10001: 100%|██████████| 10/10 [00:00<00:00, 12.33it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 241/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 241/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 241/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.848]
+Epoch 241/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.849]
+Epoch 241/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.853]
+Epoch 241/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.848]
+Epoch 241/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.86] 
+Epoch 241/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.847]
+Epoch 241/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.847]
+Epoch 241/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.854]
+Epoch 241/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.859]
+Epoch 241/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.853]
+Epoch 241/10001:  60%|██████    | 6/10 [00:00<00:00, 13.14it/s, Loss=0.85] 
+Epoch 241/10001: 100%|██████████| 10/10 [00:00<00:00, 12.83it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 242/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 242/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 242/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.843]
+Epoch 242/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.849]
+Epoch 242/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.844]
+Epoch 242/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.848]
+Epoch 242/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.857]
+Epoch 242/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.854]
+Epoch 242/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.854]
+Epoch 242/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.858]
+Epoch 242/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.85] 
+Epoch 242/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.843]
+Epoch 242/10001:  60%|██████    | 6/10 [00:00<00:00, 15.52it/s, Loss=0.85] 
+Epoch 242/10001: 100%|██████████| 10/10 [00:00<00:00, 14.82it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 243/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 243/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 243/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.846]
+Epoch 243/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.85] 
+Epoch 243/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.855]
+Epoch 243/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.847]
+Epoch 243/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.854]
+Epoch 243/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.854]
+Epoch 243/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.849]
+Epoch 243/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.85] 
+Epoch 243/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.845]
+Epoch 243/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.849]
+Epoch 243/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.851]
+Epoch 243/10001: 100%|██████████| 10/10 [00:00<00:00, 14.52it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 244/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 244/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 244/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.856]
+Epoch 244/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.851]
+Epoch 244/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.849]
+Epoch 244/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.856]
+Epoch 244/10001:  40%|████      | 4/10 [00:00<00:00, 10.45it/s, Loss=0.856]
+Epoch 244/10001:  40%|████      | 4/10 [00:00<00:00, 10.45it/s, Loss=0.85] 
+Epoch 244/10001:  40%|████      | 4/10 [00:00<00:00, 10.45it/s, Loss=0.85]
+Epoch 244/10001:  40%|████      | 4/10 [00:00<00:00, 10.45it/s, Loss=0.85]
+Epoch 244/10001:  40%|████      | 4/10 [00:00<00:00, 10.45it/s, Loss=0.85]
+Epoch 244/10001:  80%|████████  | 8/10 [00:00<00:00, 17.92it/s, Loss=0.85]
+Epoch 244/10001:  80%|████████  | 8/10 [00:00<00:00, 17.92it/s, Loss=0.847]
+Epoch 244/10001:  80%|████████  | 8/10 [00:00<00:00, 17.92it/s, Loss=0.86] 
+Epoch 244/10001: 100%|██████████| 10/10 [00:00<00:00, 13.06it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 245/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 245/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 245/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.852]
+Epoch 245/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.842]
+Epoch 245/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.848]
+Epoch 245/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.848]
+Epoch 245/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.852]
+Epoch 245/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.847]
+Epoch 245/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.847]
+Epoch 245/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.854]
+Epoch 245/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.854]
+Epoch 245/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.848]
+Epoch 245/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.845]
+Epoch 245/10001: 100%|██████████| 10/10 [00:00<00:00, 16.83it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 246/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 246/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 246/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.849]
+Epoch 246/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.847]
+Epoch 246/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.857]
+Epoch 246/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.859]
+Epoch 246/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.855]
+Epoch 246/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.855]
+Epoch 246/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.854]
+Epoch 246/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.848]
+Epoch 246/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.849]
+Epoch 246/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.85] 
+Epoch 246/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.849]
+Epoch 246/10001: 100%|██████████| 10/10 [00:00<00:00, 13.87it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 247/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 247/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 247/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.848]
+Epoch 247/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.86] 
+Epoch 247/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.856]
+Epoch 247/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.848]
+Epoch 247/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.846]
+Epoch 247/10001:  50%|█████     | 5/10 [00:00<00:00, 13.51it/s, Loss=0.846]
+Epoch 247/10001:  50%|█████     | 5/10 [00:00<00:00, 13.51it/s, Loss=0.838]
+Epoch 247/10001:  50%|█████     | 5/10 [00:00<00:00, 13.51it/s, Loss=0.856]
+Epoch 247/10001:  50%|█████     | 5/10 [00:00<00:00, 13.51it/s, Loss=0.855]
+Epoch 247/10001:  50%|█████     | 5/10 [00:00<00:00, 13.51it/s, Loss=0.855]
+Epoch 247/10001:  50%|█████     | 5/10 [00:00<00:00, 13.51it/s, Loss=0.851]
+Epoch 247/10001: 100%|██████████| 10/10 [00:00<00:00, 22.75it/s, Loss=0.851]
+Epoch 247/10001: 100%|██████████| 10/10 [00:00<00:00, 14.64it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 248/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 248/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 248/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.847]
+Epoch 248/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.848]
+Epoch 248/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.86] 
+Epoch 248/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.853]
+Epoch 248/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.854]
+Epoch 248/10001:  50%|█████     | 5/10 [00:00<00:00, 10.67it/s, Loss=0.854]
+Epoch 248/10001:  50%|█████     | 5/10 [00:00<00:00, 10.67it/s, Loss=0.851]
+Epoch 248/10001:  50%|█████     | 5/10 [00:00<00:00, 10.67it/s, Loss=0.849]
+Epoch 248/10001:  50%|█████     | 5/10 [00:00<00:00, 10.67it/s, Loss=0.851]
+Epoch 248/10001:  50%|█████     | 5/10 [00:00<00:00, 10.67it/s, Loss=0.851]
+Epoch 248/10001:  50%|█████     | 5/10 [00:00<00:00, 10.67it/s, Loss=0.854]
+Epoch 248/10001: 100%|██████████| 10/10 [00:00<00:00, 20.27it/s, Loss=0.854]
+Epoch 248/10001: 100%|██████████| 10/10 [00:00<00:00, 12.34it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 249/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 249/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 249/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.85]
+Epoch 249/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.845]
+Epoch 249/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.845]
+Epoch 249/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.855]
+Epoch 249/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.855]
+Epoch 249/10001:  50%|█████     | 5/10 [00:00<00:00, 11.61it/s, Loss=0.855]
+Epoch 249/10001:  50%|█████     | 5/10 [00:00<00:00, 11.61it/s, Loss=0.851]
+Epoch 249/10001:  50%|█████     | 5/10 [00:00<00:00, 11.61it/s, Loss=0.855]
+Epoch 249/10001:  50%|█████     | 5/10 [00:00<00:00, 11.61it/s, Loss=0.85] 
+Epoch 249/10001:  50%|█████     | 5/10 [00:00<00:00, 11.61it/s, Loss=0.837]
+Epoch 249/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.66it/s, Loss=0.837]
+Epoch 249/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.66it/s, Loss=0.852]
+Epoch 249/10001: 100%|██████████| 10/10 [00:00<00:00, 12.87it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 250/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 250/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 250/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.847]
+Epoch 250/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.858]
+Epoch 250/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.849]
+Epoch 250/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.85] 
+Epoch 250/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.852]
+Epoch 250/10001:  50%|█████     | 5/10 [00:00<00:00, 12.41it/s, Loss=0.852]
+Epoch 250/10001:  50%|█████     | 5/10 [00:00<00:00, 12.41it/s, Loss=0.851]
+Epoch 250/10001:  50%|█████     | 5/10 [00:00<00:00, 12.41it/s, Loss=0.854]
+Epoch 250/10001:  50%|█████     | 5/10 [00:00<00:00, 12.41it/s, Loss=0.845]
+Epoch 250/10001:  50%|█████     | 5/10 [00:00<00:00, 12.41it/s, Loss=0.849]
+Epoch 250/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.36it/s, Loss=0.849]
+Epoch 250/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.36it/s, Loss=0.855]
+Epoch 250/10001: 100%|██████████| 10/10 [00:00<00:00, 13.10it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 251/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 251/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 251/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.846]
+Epoch 251/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.842]
+Epoch 251/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.852]
+Epoch 251/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.847]
+Epoch 251/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.853]
+Epoch 251/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 251/10001:  60%|██████    | 6/10 [00:00<00:00, 14.11it/s, Loss=0.851]
+Epoch 251/10001:  60%|██████    | 6/10 [00:00<00:00, 14.11it/s, Loss=0.849]
+Epoch 251/10001:  60%|██████    | 6/10 [00:00<00:00, 14.11it/s, Loss=0.847]
+Epoch 251/10001:  60%|██████    | 6/10 [00:00<00:00, 14.11it/s, Loss=0.849]
+Epoch 251/10001:  60%|██████    | 6/10 [00:00<00:00, 14.11it/s, Loss=0.855]
+Epoch 251/10001: 100%|██████████| 10/10 [00:00<00:00, 14.01it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 252/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 252/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 252/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.854]
+Epoch 252/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.847]
+Epoch 252/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.846]
+Epoch 252/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.854]
+Epoch 252/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.856]
+Epoch 252/10001:  50%|█████     | 5/10 [00:00<00:00, 12.49it/s, Loss=0.856]
+Epoch 252/10001:  50%|█████     | 5/10 [00:00<00:00, 12.49it/s, Loss=0.849]
+Epoch 252/10001:  50%|█████     | 5/10 [00:00<00:00, 12.49it/s, Loss=0.846]
+Epoch 252/10001:  50%|█████     | 5/10 [00:00<00:00, 12.49it/s, Loss=0.849]
+Epoch 252/10001:  50%|█████     | 5/10 [00:00<00:00, 12.49it/s, Loss=0.849]
+Epoch 252/10001:  50%|█████     | 5/10 [00:00<00:00, 12.49it/s, Loss=0.849]
+Epoch 252/10001: 100%|██████████| 10/10 [00:00<00:00, 14.44it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 253/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 253/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 253/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.853]
+Epoch 253/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.858]
+Epoch 253/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.848]
+Epoch 253/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.848]
+Epoch 253/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.859]
+Epoch 253/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.844]
+Epoch 253/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.844]
+Epoch 253/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.851]
+Epoch 253/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.848]
+Epoch 253/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.856]
+Epoch 253/10001:  60%|██████    | 6/10 [00:00<00:00, 16.41it/s, Loss=0.856]
+Epoch 253/10001: 100%|██████████| 10/10 [00:00<00:00, 15.79it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 254/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 254/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 254/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.851]
+Epoch 254/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.858]
+Epoch 254/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.85] 
+Epoch 254/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.847]
+Epoch 254/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.851]
+Epoch 254/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.864]
+Epoch 254/10001:  60%|██████    | 6/10 [00:00<00:00, 16.04it/s, Loss=0.864]
+Epoch 254/10001:  60%|██████    | 6/10 [00:00<00:00, 16.04it/s, Loss=0.859]
+Epoch 254/10001:  60%|██████    | 6/10 [00:00<00:00, 16.04it/s, Loss=0.848]
+Epoch 254/10001:  60%|██████    | 6/10 [00:00<00:00, 16.04it/s, Loss=0.851]
+Epoch 254/10001:  60%|██████    | 6/10 [00:00<00:00, 16.04it/s, Loss=0.86] 
+Epoch 254/10001: 100%|██████████| 10/10 [00:00<00:00, 15.48it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 255/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 255/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 255/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.855]
+Epoch 255/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.85] 
+Epoch 255/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.855]
+Epoch 255/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.851]
+Epoch 255/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 255/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.847]
+Epoch 255/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.847]
+Epoch 255/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.854]
+Epoch 255/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.851]
+Epoch 255/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.848]
+Epoch 255/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.851]
+Epoch 255/10001: 100%|██████████| 10/10 [00:00<00:00, 14.05it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 256/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 256/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 256/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.852]
+Epoch 256/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.853]
+Epoch 256/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.849]
+Epoch 256/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.858]
+Epoch 256/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.852]
+Epoch 256/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.851]
+Epoch 256/10001:  60%|██████    | 6/10 [00:00<00:00, 16.24it/s, Loss=0.851]
+Epoch 256/10001:  60%|██████    | 6/10 [00:00<00:00, 16.24it/s, Loss=0.848]
+Epoch 256/10001:  60%|██████    | 6/10 [00:00<00:00, 16.24it/s, Loss=0.854]
+Epoch 256/10001:  60%|██████    | 6/10 [00:00<00:00, 16.24it/s, Loss=0.847]
+Epoch 256/10001:  60%|██████    | 6/10 [00:00<00:00, 16.24it/s, Loss=0.851]
+Epoch 256/10001: 100%|██████████| 10/10 [00:00<00:00, 15.64it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 257/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 257/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 257/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.85]
+Epoch 257/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.85]
+Epoch 257/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.849]
+Epoch 257/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.845]
+Epoch 257/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.845]
+Epoch 257/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.856]
+Epoch 257/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.842]
+Epoch 257/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.857]
+Epoch 257/10001:  40%|████      | 4/10 [00:00<00:00,  9.03it/s, Loss=0.85] 
+Epoch 257/10001:  80%|████████  | 8/10 [00:00<00:00, 16.57it/s, Loss=0.85]
+Epoch 257/10001:  80%|████████  | 8/10 [00:00<00:00, 16.57it/s, Loss=0.853]
+Epoch 257/10001:  80%|████████  | 8/10 [00:00<00:00, 16.57it/s, Loss=0.847]
+Epoch 257/10001: 100%|██████████| 10/10 [00:00<00:00, 11.71it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 258/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 258/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.841]
+Epoch 258/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.841]
+Epoch 258/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.858]
+Epoch 258/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.848]
+Epoch 258/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.849]
+Epoch 258/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.862]
+Epoch 258/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.856]
+Epoch 258/10001:  60%|██████    | 6/10 [00:00<00:00, 13.47it/s, Loss=0.856]
+Epoch 258/10001:  60%|██████    | 6/10 [00:00<00:00, 13.47it/s, Loss=0.856]
+Epoch 258/10001:  60%|██████    | 6/10 [00:00<00:00, 13.47it/s, Loss=0.859]
+Epoch 258/10001:  60%|██████    | 6/10 [00:00<00:00, 13.47it/s, Loss=0.852]
+Epoch 258/10001:  60%|██████    | 6/10 [00:00<00:00, 13.47it/s, Loss=0.852]
+Epoch 258/10001: 100%|██████████| 10/10 [00:00<00:00, 12.96it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 259/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 259/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 259/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.849]
+Epoch 259/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 259/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.843]
+Epoch 259/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.849]
+Epoch 259/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.857]
+Epoch 259/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.857]
+Epoch 259/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.857]
+Epoch 259/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.853]
+Epoch 259/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.859]
+Epoch 259/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.854]
+Epoch 259/10001:  60%|██████    | 6/10 [00:00<00:00, 13.21it/s, Loss=0.859]
+Epoch 259/10001: 100%|██████████| 10/10 [00:00<00:00, 19.82it/s, Loss=0.859]
+Epoch 259/10001: 100%|██████████| 10/10 [00:00<00:00, 12.94it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 260/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 260/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 260/10001:  10%|█         | 1/10 [00:00<00:02,  3.10it/s, Loss=0.848]
+Epoch 260/10001:  10%|█         | 1/10 [00:00<00:02,  3.10it/s, Loss=0.852]
+Epoch 260/10001:  10%|█         | 1/10 [00:00<00:02,  3.10it/s, Loss=0.854]
+Epoch 260/10001:  10%|█         | 1/10 [00:00<00:02,  3.10it/s, Loss=0.854]
+Epoch 260/10001:  10%|█         | 1/10 [00:00<00:02,  3.10it/s, Loss=0.853]
+Epoch 260/10001:  10%|█         | 1/10 [00:00<00:02,  3.10it/s, Loss=0.85] 
+Epoch 260/10001:  60%|██████    | 6/10 [00:00<00:00, 16.85it/s, Loss=0.85]
+Epoch 260/10001:  60%|██████    | 6/10 [00:00<00:00, 16.85it/s, Loss=0.853]
+Epoch 260/10001:  60%|██████    | 6/10 [00:00<00:00, 16.85it/s, Loss=0.854]
+Epoch 260/10001:  60%|██████    | 6/10 [00:00<00:00, 16.85it/s, Loss=0.858]
+Epoch 260/10001:  60%|██████    | 6/10 [00:00<00:00, 16.85it/s, Loss=0.847]
+Epoch 260/10001: 100%|██████████| 10/10 [00:00<00:00, 15.64it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 261/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 261/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.844]
+Epoch 261/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.844]
+Epoch 261/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.855]
+Epoch 261/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.851]
+Epoch 261/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.851]
+Epoch 261/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.857]
+Epoch 261/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.851]
+Epoch 261/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.844]
+Epoch 261/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.855]
+Epoch 261/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.845]
+Epoch 261/10001:  90%|█████████ | 9/10 [00:00<00:00, 24.15it/s, Loss=0.845]
+Epoch 261/10001:  90%|█████████ | 9/10 [00:00<00:00, 24.15it/s, Loss=0.852]
+Epoch 261/10001: 100%|██████████| 10/10 [00:00<00:00, 16.96it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 262/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 262/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 262/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.85]
+Epoch 262/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.86]
+Epoch 262/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.85]
+Epoch 262/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.859]
+Epoch 262/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.853]
+Epoch 262/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.85] 
+Epoch 262/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.854]
+Epoch 262/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.863]
+Epoch 262/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.851]
+Epoch 262/10001:  90%|█████████ | 9/10 [00:00<00:00, 24.09it/s, Loss=0.851]
+Epoch 262/10001:  90%|█████████ | 9/10 [00:00<00:00, 24.09it/s, Loss=0.841]
+Epoch 262/10001: 100%|██████████| 10/10 [00:00<00:00, 16.93it/s, Loss=0.841]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 263/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 263/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 263/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.851]
+Epoch 263/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.857]
+Epoch 263/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.852]
+Epoch 263/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.856]
+Epoch 263/10001:  40%|████      | 4/10 [00:00<00:00,  9.26it/s, Loss=0.856]
+Epoch 263/10001:  40%|████      | 4/10 [00:00<00:00,  9.26it/s, Loss=0.855]
+Epoch 263/10001:  40%|████      | 4/10 [00:00<00:00,  9.26it/s, Loss=0.849]
+Epoch 263/10001:  40%|████      | 4/10 [00:00<00:00,  9.26it/s, Loss=0.847]
+Epoch 263/10001:  40%|████      | 4/10 [00:00<00:00,  9.26it/s, Loss=0.848]
+Epoch 263/10001:  80%|████████  | 8/10 [00:00<00:00, 16.62it/s, Loss=0.848]
+Epoch 263/10001:  80%|████████  | 8/10 [00:00<00:00, 16.62it/s, Loss=0.852]
+Epoch 263/10001:  80%|████████  | 8/10 [00:00<00:00, 16.62it/s, Loss=0.858]
+Epoch 263/10001: 100%|██████████| 10/10 [00:00<00:00, 12.41it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 264/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 264/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 264/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.85]
+Epoch 264/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.85]
+Epoch 264/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.852]
+Epoch 264/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.853]
+Epoch 264/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.849]
+Epoch 264/10001:  50%|█████     | 5/10 [00:00<00:00, 13.41it/s, Loss=0.849]
+Epoch 264/10001:  50%|█████     | 5/10 [00:00<00:00, 13.41it/s, Loss=0.852]
+Epoch 264/10001:  50%|█████     | 5/10 [00:00<00:00, 13.41it/s, Loss=0.857]
+Epoch 264/10001:  50%|█████     | 5/10 [00:00<00:00, 13.41it/s, Loss=0.855]
+Epoch 264/10001:  50%|█████     | 5/10 [00:00<00:00, 13.41it/s, Loss=0.849]
+Epoch 264/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.04it/s, Loss=0.849]
+Epoch 264/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.04it/s, Loss=0.85] 
+Epoch 264/10001: 100%|██████████| 10/10 [00:00<00:00, 14.27it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 265/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 265/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 265/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.851]
+Epoch 265/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.851]
+Epoch 265/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.856]
+Epoch 265/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.864]
+Epoch 265/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.849]
+Epoch 265/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.849]
+Epoch 265/10001:  60%|██████    | 6/10 [00:00<00:00, 15.60it/s, Loss=0.849]
+Epoch 265/10001:  60%|██████    | 6/10 [00:00<00:00, 15.60it/s, Loss=0.852]
+Epoch 265/10001:  60%|██████    | 6/10 [00:00<00:00, 15.60it/s, Loss=0.85] 
+Epoch 265/10001:  60%|██████    | 6/10 [00:00<00:00, 15.60it/s, Loss=0.845]
+Epoch 265/10001:  60%|██████    | 6/10 [00:00<00:00, 15.60it/s, Loss=0.84] 
+Epoch 265/10001: 100%|██████████| 10/10 [00:00<00:00, 15.33it/s, Loss=0.84]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 266/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 266/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 266/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.849]
+Epoch 266/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.855]
+Epoch 266/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.85] 
+Epoch 266/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.849]
+Epoch 266/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.854]
+Epoch 266/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.842]
+Epoch 266/10001:  60%|██████    | 6/10 [00:00<00:00, 15.45it/s, Loss=0.842]
+Epoch 266/10001:  60%|██████    | 6/10 [00:00<00:00, 15.45it/s, Loss=0.857]
+Epoch 266/10001:  60%|██████    | 6/10 [00:00<00:00, 15.45it/s, Loss=0.849]
+Epoch 266/10001:  60%|██████    | 6/10 [00:00<00:00, 15.45it/s, Loss=0.851]
+Epoch 266/10001:  60%|██████    | 6/10 [00:00<00:00, 15.45it/s, Loss=0.861]
+Epoch 266/10001: 100%|██████████| 10/10 [00:00<00:00, 15.11it/s, Loss=0.861]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 267/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 267/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 267/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.847]
+Epoch 267/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.848]
+Epoch 267/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.853]
+Epoch 267/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.856]
+Epoch 267/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.848]
+Epoch 267/10001:  50%|█████     | 5/10 [00:00<00:00, 12.91it/s, Loss=0.848]
+Epoch 267/10001:  50%|█████     | 5/10 [00:00<00:00, 12.91it/s, Loss=0.853]
+Epoch 267/10001:  50%|█████     | 5/10 [00:00<00:00, 12.91it/s, Loss=0.85] 
+Epoch 267/10001:  50%|█████     | 5/10 [00:00<00:00, 12.91it/s, Loss=0.849]
+Epoch 267/10001:  50%|█████     | 5/10 [00:00<00:00, 12.91it/s, Loss=0.857]
+Epoch 267/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.69it/s, Loss=0.857]
+Epoch 267/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.69it/s, Loss=0.854]
+Epoch 267/10001: 100%|██████████| 10/10 [00:00<00:00, 13.57it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 268/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 268/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 268/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.852]
+Epoch 268/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.847]
+Epoch 268/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.848]
+Epoch 268/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.854]
+Epoch 268/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.845]
+Epoch 268/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.85] 
+Epoch 268/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.854]
+Epoch 268/10001:  70%|███████   | 7/10 [00:00<00:00, 15.85it/s, Loss=0.854]
+Epoch 268/10001:  70%|███████   | 7/10 [00:00<00:00, 15.85it/s, Loss=0.854]
+Epoch 268/10001:  70%|███████   | 7/10 [00:00<00:00, 15.85it/s, Loss=0.854]
+Epoch 268/10001:  70%|███████   | 7/10 [00:00<00:00, 15.85it/s, Loss=0.85] 
+Epoch 268/10001: 100%|██████████| 10/10 [00:00<00:00, 14.04it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 269/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 269/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 269/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.847]
+Epoch 269/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.847]
+Epoch 269/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.853]
+Epoch 269/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.842]
+Epoch 269/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.852]
+Epoch 269/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.85] 
+Epoch 269/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.85]
+Epoch 269/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.858]
+Epoch 269/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.85] 
+Epoch 269/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.853]
+Epoch 269/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.859]
+Epoch 269/10001: 100%|██████████| 10/10 [00:00<00:00, 15.36it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 270/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 270/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 270/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.847]
+Epoch 270/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.848]
+Epoch 270/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.859]
+Epoch 270/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.856]
+Epoch 270/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.852]
+Epoch 270/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.844]
+Epoch 270/10001:  60%|██████    | 6/10 [00:00<00:00, 14.55it/s, Loss=0.844]
+Epoch 270/10001:  60%|██████    | 6/10 [00:00<00:00, 14.55it/s, Loss=0.848]
+Epoch 270/10001:  60%|██████    | 6/10 [00:00<00:00, 14.55it/s, Loss=0.842]
+Epoch 270/10001:  60%|██████    | 6/10 [00:00<00:00, 14.55it/s, Loss=0.845]
+Epoch 270/10001:  60%|██████    | 6/10 [00:00<00:00, 14.55it/s, Loss=0.85] 
+Epoch 270/10001: 100%|██████████| 10/10 [00:00<00:00, 14.50it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 271/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 271/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 271/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.85]
+Epoch 271/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.853]
+Epoch 271/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.852]
+Epoch 271/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.845]
+Epoch 271/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.848]
+Epoch 271/10001:  50%|█████     | 5/10 [00:00<00:00, 13.17it/s, Loss=0.848]
+Epoch 271/10001:  50%|█████     | 5/10 [00:00<00:00, 13.17it/s, Loss=0.851]
+Epoch 271/10001:  50%|█████     | 5/10 [00:00<00:00, 13.17it/s, Loss=0.855]
+Epoch 271/10001:  50%|█████     | 5/10 [00:00<00:00, 13.17it/s, Loss=0.847]
+Epoch 271/10001:  50%|█████     | 5/10 [00:00<00:00, 13.17it/s, Loss=0.846]
+Epoch 271/10001:  50%|█████     | 5/10 [00:00<00:00, 13.17it/s, Loss=0.851]
+Epoch 271/10001: 100%|██████████| 10/10 [00:00<00:00, 15.19it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 272/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 272/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 272/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.851]
+Epoch 272/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.856]
+Epoch 272/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.853]
+Epoch 272/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.854]
+Epoch 272/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.846]
+Epoch 272/10001:  50%|█████     | 5/10 [00:00<00:00, 13.40it/s, Loss=0.846]
+Epoch 272/10001:  50%|█████     | 5/10 [00:00<00:00, 13.40it/s, Loss=0.85] 
+Epoch 272/10001:  50%|█████     | 5/10 [00:00<00:00, 13.40it/s, Loss=0.849]
+Epoch 272/10001:  50%|█████     | 5/10 [00:00<00:00, 13.40it/s, Loss=0.855]
+Epoch 272/10001:  50%|█████     | 5/10 [00:00<00:00, 13.40it/s, Loss=0.842]
+Epoch 272/10001:  50%|█████     | 5/10 [00:00<00:00, 13.40it/s, Loss=0.849]
+Epoch 272/10001: 100%|██████████| 10/10 [00:00<00:00, 22.41it/s, Loss=0.849]
+Epoch 272/10001: 100%|██████████| 10/10 [00:00<00:00, 13.87it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 273/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 273/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 273/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.855]
+Epoch 273/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.853]
+Epoch 273/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.848]
+Epoch 273/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.847]
+Epoch 273/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.853]
+Epoch 273/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.85] 
+Epoch 273/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.852]
+Epoch 273/10001:  70%|███████   | 7/10 [00:00<00:00, 16.27it/s, Loss=0.852]
+Epoch 273/10001:  70%|███████   | 7/10 [00:00<00:00, 16.27it/s, Loss=0.845]
+Epoch 273/10001:  70%|███████   | 7/10 [00:00<00:00, 16.27it/s, Loss=0.856]
+Epoch 273/10001:  70%|███████   | 7/10 [00:00<00:00, 16.27it/s, Loss=0.848]
+Epoch 273/10001: 100%|██████████| 10/10 [00:00<00:00, 13.72it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 274/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 274/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 274/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.85]
+Epoch 274/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.848]
+Epoch 274/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.844]
+Epoch 274/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.855]
+Epoch 274/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.854]
+Epoch 274/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.854]
+Epoch 274/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.85] 
+Epoch 274/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.852]
+Epoch 274/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.86] 
+Epoch 274/10001:  50%|█████     | 5/10 [00:00<00:00, 10.79it/s, Loss=0.85]
+Epoch 274/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.32it/s, Loss=0.85]
+Epoch 274/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.32it/s, Loss=0.853]
+Epoch 274/10001: 100%|██████████| 10/10 [00:00<00:00, 12.18it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 275/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 275/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 275/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.849]
+Epoch 275/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.846]
+Epoch 275/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.859]
+Epoch 275/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.86] 
+Epoch 275/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.852]
+Epoch 275/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.855]
+Epoch 275/10001:  60%|██████    | 6/10 [00:00<00:00, 14.16it/s, Loss=0.855]
+Epoch 275/10001:  60%|██████    | 6/10 [00:00<00:00, 14.16it/s, Loss=0.86] 
+Epoch 275/10001:  60%|██████    | 6/10 [00:00<00:00, 14.16it/s, Loss=0.848]
+Epoch 275/10001:  60%|██████    | 6/10 [00:00<00:00, 14.16it/s, Loss=0.848]
+Epoch 275/10001:  60%|██████    | 6/10 [00:00<00:00, 14.16it/s, Loss=0.854]
+Epoch 275/10001: 100%|██████████| 10/10 [00:00<00:00, 20.42it/s, Loss=0.854]
+Epoch 275/10001: 100%|██████████| 10/10 [00:00<00:00, 13.34it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 276/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 276/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 276/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.852]
+Epoch 276/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.85] 
+Epoch 276/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.845]
+Epoch 276/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.847]
+Epoch 276/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.856]
+Epoch 276/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.853]
+Epoch 276/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.85] 
+Epoch 276/10001:  10%|█         | 1/10 [00:00<00:02,  3.03it/s, Loss=0.86]
+Epoch 276/10001:  80%|████████  | 8/10 [00:00<00:00, 22.47it/s, Loss=0.86]
+Epoch 276/10001:  80%|████████  | 8/10 [00:00<00:00, 22.47it/s, Loss=0.853]
+Epoch 276/10001:  80%|████████  | 8/10 [00:00<00:00, 22.47it/s, Loss=0.855]
+Epoch 276/10001: 100%|██████████| 10/10 [00:00<00:00, 17.39it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 277/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 277/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 277/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.856]
+Epoch 277/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.846]
+Epoch 277/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.856]
+Epoch 277/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.851]
+Epoch 277/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.851]
+Epoch 277/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.851]
+Epoch 277/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.85] 
+Epoch 277/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.849]
+Epoch 277/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.853]
+Epoch 277/10001:  50%|█████     | 5/10 [00:00<00:00, 12.16it/s, Loss=0.849]
+Epoch 277/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.90it/s, Loss=0.849]
+Epoch 277/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.90it/s, Loss=0.846]
+Epoch 277/10001: 100%|██████████| 10/10 [00:00<00:00, 13.41it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 278/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 278/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.842]
+Epoch 278/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.842]
+Epoch 278/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.85] 
+Epoch 278/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.851]
+Epoch 278/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.852]
+Epoch 278/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.852]
+Epoch 278/10001:  50%|█████     | 5/10 [00:00<00:00, 12.25it/s, Loss=0.852]
+Epoch 278/10001:  50%|█████     | 5/10 [00:00<00:00, 12.25it/s, Loss=0.844]
+Epoch 278/10001:  50%|█████     | 5/10 [00:00<00:00, 12.25it/s, Loss=0.845]
+Epoch 278/10001:  50%|█████     | 5/10 [00:00<00:00, 12.25it/s, Loss=0.847]
+Epoch 278/10001:  50%|█████     | 5/10 [00:00<00:00, 12.25it/s, Loss=0.845]
+Epoch 278/10001:  50%|█████     | 5/10 [00:00<00:00, 12.25it/s, Loss=0.855]
+Epoch 278/10001: 100%|██████████| 10/10 [00:00<00:00, 13.77it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 279/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 279/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 279/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.848]
+Epoch 279/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.849]
+Epoch 279/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.854]
+Epoch 279/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.854]
+Epoch 279/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.861]
+Epoch 279/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.85] 
+Epoch 279/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.85]
+Epoch 279/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.85]
+Epoch 279/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.844]
+Epoch 279/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.846]
+Epoch 279/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.847]
+Epoch 279/10001: 100%|██████████| 10/10 [00:00<00:00, 13.87it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 280/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 280/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 280/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.854]
+Epoch 280/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.848]
+Epoch 280/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.846]
+Epoch 280/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.847]
+Epoch 280/10001:  10%|█         | 1/10 [00:00<00:03,  2.55it/s, Loss=0.844]
+Epoch 280/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.844]
+Epoch 280/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.851]
+Epoch 280/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.851]
+Epoch 280/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.853]
+Epoch 280/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.856]
+Epoch 280/10001:  50%|█████     | 5/10 [00:00<00:00, 11.97it/s, Loss=0.849]
+Epoch 280/10001: 100%|██████████| 10/10 [00:00<00:00, 13.64it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 281/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 281/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 281/10001:  10%|█         | 1/10 [00:00<00:04,  2.08it/s, Loss=0.852]
+Epoch 281/10001:  10%|█         | 1/10 [00:00<00:04,  2.08it/s, Loss=0.851]
+Epoch 281/10001:  10%|█         | 1/10 [00:00<00:04,  2.08it/s, Loss=0.853]
+Epoch 281/10001:  10%|█         | 1/10 [00:00<00:04,  2.08it/s, Loss=0.848]
+Epoch 281/10001:  10%|█         | 1/10 [00:00<00:04,  2.08it/s, Loss=0.853]
+Epoch 281/10001:  10%|█         | 1/10 [00:00<00:04,  2.08it/s, Loss=0.85] 
+Epoch 281/10001:  60%|██████    | 6/10 [00:00<00:00, 12.74it/s, Loss=0.85]
+Epoch 281/10001:  60%|██████    | 6/10 [00:00<00:00, 12.74it/s, Loss=0.863]
+Epoch 281/10001:  60%|██████    | 6/10 [00:00<00:00, 12.74it/s, Loss=0.845]
+Epoch 281/10001:  60%|██████    | 6/10 [00:00<00:00, 12.74it/s, Loss=0.857]
+Epoch 281/10001:  60%|██████    | 6/10 [00:00<00:00, 12.74it/s, Loss=0.85] 
+Epoch 281/10001: 100%|██████████| 10/10 [00:00<00:00, 12.79it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 282/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 282/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 282/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.853]
+Epoch 282/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.857]
+Epoch 282/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.848]
+Epoch 282/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.854]
+Epoch 282/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.853]
+Epoch 282/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.848]
+Epoch 282/10001:  60%|██████    | 6/10 [00:00<00:00, 16.18it/s, Loss=0.848]
+Epoch 282/10001:  60%|██████    | 6/10 [00:00<00:00, 16.18it/s, Loss=0.851]
+Epoch 282/10001:  60%|██████    | 6/10 [00:00<00:00, 16.18it/s, Loss=0.848]
+Epoch 282/10001:  60%|██████    | 6/10 [00:00<00:00, 16.18it/s, Loss=0.851]
+Epoch 282/10001:  60%|██████    | 6/10 [00:00<00:00, 16.18it/s, Loss=0.845]
+Epoch 282/10001: 100%|██████████| 10/10 [00:00<00:00, 15.42it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 283/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 283/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 283/10001:  10%|█         | 1/10 [00:00<00:02,  3.18it/s, Loss=0.856]
+Epoch 283/10001:  10%|█         | 1/10 [00:00<00:02,  3.18it/s, Loss=0.852]
+Epoch 283/10001:  10%|█         | 1/10 [00:00<00:02,  3.18it/s, Loss=0.849]
+Epoch 283/10001:  10%|█         | 1/10 [00:00<00:02,  3.18it/s, Loss=0.849]
+Epoch 283/10001:  10%|█         | 1/10 [00:00<00:02,  3.18it/s, Loss=0.852]
+Epoch 283/10001:  10%|█         | 1/10 [00:00<00:02,  3.18it/s, Loss=0.844]
+Epoch 283/10001:  60%|██████    | 6/10 [00:00<00:00, 17.39it/s, Loss=0.844]
+Epoch 283/10001:  60%|██████    | 6/10 [00:00<00:00, 17.39it/s, Loss=0.853]
+Epoch 283/10001:  60%|██████    | 6/10 [00:00<00:00, 17.39it/s, Loss=0.857]
+Epoch 283/10001:  60%|██████    | 6/10 [00:00<00:00, 17.39it/s, Loss=0.853]
+Epoch 283/10001:  60%|██████    | 6/10 [00:00<00:00, 17.39it/s, Loss=0.856]
+Epoch 283/10001: 100%|██████████| 10/10 [00:00<00:00, 17.03it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 284/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 284/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.844]
+Epoch 284/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.844]
+Epoch 284/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.857]
+Epoch 284/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.852]
+Epoch 284/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.855]
+Epoch 284/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.843]
+Epoch 284/10001:  50%|█████     | 5/10 [00:00<00:00, 12.73it/s, Loss=0.843]
+Epoch 284/10001:  50%|█████     | 5/10 [00:00<00:00, 12.73it/s, Loss=0.853]
+Epoch 284/10001:  50%|█████     | 5/10 [00:00<00:00, 12.73it/s, Loss=0.852]
+Epoch 284/10001:  50%|█████     | 5/10 [00:00<00:00, 12.73it/s, Loss=0.84] 
+Epoch 284/10001:  50%|█████     | 5/10 [00:00<00:00, 12.73it/s, Loss=0.85]
+Epoch 284/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.76it/s, Loss=0.85]
+Epoch 284/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.76it/s, Loss=0.848]
+Epoch 284/10001: 100%|██████████| 10/10 [00:00<00:00, 13.58it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 285/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 285/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 285/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.845]
+Epoch 285/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.854]
+Epoch 285/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.851]
+Epoch 285/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.85] 
+Epoch 285/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.843]
+Epoch 285/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.843]
+Epoch 285/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.843]
+Epoch 285/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.859]
+Epoch 285/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.841]
+Epoch 285/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.847]
+Epoch 285/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.846]
+Epoch 285/10001: 100%|██████████| 10/10 [00:00<00:00, 13.06it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 286/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 286/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 286/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.85]
+Epoch 286/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.841]
+Epoch 286/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.85] 
+Epoch 286/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.856]
+Epoch 286/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.853]
+Epoch 286/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.855]
+Epoch 286/10001:  60%|██████    | 6/10 [00:00<00:00, 14.01it/s, Loss=0.855]
+Epoch 286/10001:  60%|██████    | 6/10 [00:00<00:00, 14.01it/s, Loss=0.844]
+Epoch 286/10001:  60%|██████    | 6/10 [00:00<00:00, 14.01it/s, Loss=0.849]
+Epoch 286/10001:  60%|██████    | 6/10 [00:00<00:00, 14.01it/s, Loss=0.844]
+Epoch 286/10001:  60%|██████    | 6/10 [00:00<00:00, 14.01it/s, Loss=0.852]
+Epoch 286/10001: 100%|██████████| 10/10 [00:00<00:00, 13.69it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 287/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 287/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 287/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.852]
+Epoch 287/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.844]
+Epoch 287/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.844]
+Epoch 287/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.845]
+Epoch 287/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.85] 
+Epoch 287/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.848]
+Epoch 287/10001:  60%|██████    | 6/10 [00:00<00:00, 13.76it/s, Loss=0.848]
+Epoch 287/10001:  60%|██████    | 6/10 [00:00<00:00, 13.76it/s, Loss=0.852]
+Epoch 287/10001:  60%|██████    | 6/10 [00:00<00:00, 13.76it/s, Loss=0.861]
+Epoch 287/10001:  60%|██████    | 6/10 [00:00<00:00, 13.76it/s, Loss=0.85] 
+Epoch 287/10001:  60%|██████    | 6/10 [00:00<00:00, 13.76it/s, Loss=0.857]
+Epoch 287/10001: 100%|██████████| 10/10 [00:00<00:00, 13.82it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 288/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 288/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 288/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.847]
+Epoch 288/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.855]
+Epoch 288/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.849]
+Epoch 288/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.854]
+Epoch 288/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.851]
+Epoch 288/10001:  50%|█████     | 5/10 [00:00<00:00, 11.03it/s, Loss=0.851]
+Epoch 288/10001:  50%|█████     | 5/10 [00:00<00:00, 11.03it/s, Loss=0.854]
+Epoch 288/10001:  50%|█████     | 5/10 [00:00<00:00, 11.03it/s, Loss=0.852]
+Epoch 288/10001:  50%|█████     | 5/10 [00:00<00:00, 11.03it/s, Loss=0.848]
+Epoch 288/10001:  50%|█████     | 5/10 [00:00<00:00, 11.03it/s, Loss=0.853]
+Epoch 288/10001:  50%|█████     | 5/10 [00:00<00:00, 11.03it/s, Loss=0.855]
+Epoch 288/10001: 100%|██████████| 10/10 [00:00<00:00, 12.78it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 289/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 289/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.861]
+Epoch 289/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.861]
+Epoch 289/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.851]
+Epoch 289/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.854]
+Epoch 289/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.85] 
+Epoch 289/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.85]
+Epoch 289/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.85]
+Epoch 289/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.85]
+Epoch 289/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.861]
+Epoch 289/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.855]
+Epoch 289/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.853]
+Epoch 289/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.854]
+Epoch 289/10001: 100%|██████████| 10/10 [00:00<00:00, 13.44it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 290/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 290/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 290/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.847]
+Epoch 290/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 290/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.842]
+Epoch 290/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.855]
+Epoch 290/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.858]
+Epoch 290/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 290/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.851]
+Epoch 290/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.843]
+Epoch 290/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.847]
+Epoch 290/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.854]
+Epoch 290/10001:  60%|██████    | 6/10 [00:00<00:00, 13.92it/s, Loss=0.851]
+Epoch 290/10001: 100%|██████████| 10/10 [00:00<00:00, 13.17it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 291/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 291/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 291/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.856]
+Epoch 291/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.85] 
+Epoch 291/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.854]
+Epoch 291/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.849]
+Epoch 291/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.849]
+Epoch 291/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.857]
+Epoch 291/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.846]
+Epoch 291/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.857]
+Epoch 291/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.852]
+Epoch 291/10001:  80%|████████  | 8/10 [00:00<00:00, 16.67it/s, Loss=0.852]
+Epoch 291/10001:  80%|████████  | 8/10 [00:00<00:00, 16.67it/s, Loss=0.848]
+Epoch 291/10001:  80%|████████  | 8/10 [00:00<00:00, 16.67it/s, Loss=0.854]
+Epoch 291/10001: 100%|██████████| 10/10 [00:00<00:00, 12.60it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 292/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 292/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 292/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.855]
+Epoch 292/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.857]
+Epoch 292/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.856]
+Epoch 292/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.849]
+Epoch 292/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.85] 
+Epoch 292/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.857]
+Epoch 292/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.857]
+Epoch 292/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.852]
+Epoch 292/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.852]
+Epoch 292/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.842]
+Epoch 292/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.845]
+Epoch 292/10001: 100%|██████████| 10/10 [00:00<00:00, 13.98it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 293/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 293/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 293/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.848]
+Epoch 293/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.849]
+Epoch 293/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.847]
+Epoch 293/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.851]
+Epoch 293/10001:  10%|█         | 1/10 [00:00<00:03,  2.93it/s, Loss=0.85] 
+Epoch 293/10001:  50%|█████     | 5/10 [00:00<00:00, 13.18it/s, Loss=0.85]
+Epoch 293/10001:  50%|█████     | 5/10 [00:00<00:00, 13.18it/s, Loss=0.846]
+Epoch 293/10001:  50%|█████     | 5/10 [00:00<00:00, 13.18it/s, Loss=0.854]
+Epoch 293/10001:  50%|█████     | 5/10 [00:00<00:00, 13.18it/s, Loss=0.854]
+Epoch 293/10001:  50%|█████     | 5/10 [00:00<00:00, 13.18it/s, Loss=0.85] 
+Epoch 293/10001:  50%|█████     | 5/10 [00:00<00:00, 13.18it/s, Loss=0.861]
+Epoch 293/10001: 100%|██████████| 10/10 [00:00<00:00, 15.20it/s, Loss=0.861]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 294/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 294/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 294/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.857]
+Epoch 294/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.848]
+Epoch 294/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.847]
+Epoch 294/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.852]
+Epoch 294/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.855]
+Epoch 294/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.844]
+Epoch 294/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.845]
+Epoch 294/10001:  70%|███████   | 7/10 [00:00<00:00, 17.63it/s, Loss=0.845]
+Epoch 294/10001:  70%|███████   | 7/10 [00:00<00:00, 17.63it/s, Loss=0.85] 
+Epoch 294/10001:  70%|███████   | 7/10 [00:00<00:00, 17.63it/s, Loss=0.851]
+Epoch 294/10001:  70%|███████   | 7/10 [00:00<00:00, 17.63it/s, Loss=0.851]
+Epoch 294/10001: 100%|██████████| 10/10 [00:00<00:00, 14.59it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 295/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 295/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 295/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.852]
+Epoch 295/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.852]
+Epoch 295/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.851]
+Epoch 295/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.848]
+Epoch 295/10001:  40%|████      | 4/10 [00:00<00:00,  8.46it/s, Loss=0.848]
+Epoch 295/10001:  40%|████      | 4/10 [00:00<00:00,  8.46it/s, Loss=0.852]
+Epoch 295/10001:  40%|████      | 4/10 [00:00<00:00,  8.46it/s, Loss=0.853]
+Epoch 295/10001:  40%|████      | 4/10 [00:00<00:00,  8.46it/s, Loss=0.851]
+Epoch 295/10001:  40%|████      | 4/10 [00:00<00:00,  8.46it/s, Loss=0.853]
+Epoch 295/10001:  80%|████████  | 8/10 [00:00<00:00, 15.75it/s, Loss=0.853]
+Epoch 295/10001:  80%|████████  | 8/10 [00:00<00:00, 15.75it/s, Loss=0.85] 
+Epoch 295/10001:  80%|████████  | 8/10 [00:00<00:00, 15.75it/s, Loss=0.852]
+Epoch 295/10001: 100%|██████████| 10/10 [00:00<00:00, 11.69it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 296/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 296/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.859]
+Epoch 296/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.859]
+Epoch 296/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.85] 
+Epoch 296/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.849]
+Epoch 296/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.849]
+Epoch 296/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.856]
+Epoch 296/10001:  10%|█         | 1/10 [00:00<00:03,  2.63it/s, Loss=0.846]
+Epoch 296/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.846]
+Epoch 296/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.852]
+Epoch 296/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.852]
+Epoch 296/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.85] 
+Epoch 296/10001:  60%|██████    | 6/10 [00:00<00:00, 15.47it/s, Loss=0.854]
+Epoch 296/10001: 100%|██████████| 10/10 [00:00<00:00, 15.03it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 297/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 297/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 297/10001:  10%|█         | 1/10 [00:00<00:02,  3.09it/s, Loss=0.851]
+Epoch 297/10001:  10%|█         | 1/10 [00:00<00:02,  3.09it/s, Loss=0.85] 
+Epoch 297/10001:  10%|█         | 1/10 [00:00<00:02,  3.09it/s, Loss=0.859]
+Epoch 297/10001:  10%|█         | 1/10 [00:00<00:02,  3.09it/s, Loss=0.855]
+Epoch 297/10001:  10%|█         | 1/10 [00:00<00:02,  3.09it/s, Loss=0.848]
+Epoch 297/10001:  10%|█         | 1/10 [00:00<00:02,  3.09it/s, Loss=0.853]
+Epoch 297/10001:  10%|█         | 1/10 [00:00<00:02,  3.09it/s, Loss=0.851]
+Epoch 297/10001:  10%|█         | 1/10 [00:00<00:02,  3.09it/s, Loss=0.849]
+Epoch 297/10001:  80%|████████  | 8/10 [00:00<00:00, 23.29it/s, Loss=0.849]
+Epoch 297/10001:  80%|████████  | 8/10 [00:00<00:00, 23.29it/s, Loss=0.849]
+Epoch 297/10001:  80%|████████  | 8/10 [00:00<00:00, 23.29it/s, Loss=0.849]
+Epoch 297/10001: 100%|██████████| 10/10 [00:00<00:00, 17.77it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 298/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 298/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 298/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.846]
+Epoch 298/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.858]
+Epoch 298/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.845]
+Epoch 298/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.848]
+Epoch 298/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.856]
+Epoch 298/10001:  10%|█         | 1/10 [00:00<00:02,  3.04it/s, Loss=0.855]
+Epoch 298/10001:  60%|██████    | 6/10 [00:00<00:00, 16.62it/s, Loss=0.855]
+Epoch 298/10001:  60%|██████    | 6/10 [00:00<00:00, 16.62it/s, Loss=0.85] 
+Epoch 298/10001:  60%|██████    | 6/10 [00:00<00:00, 16.62it/s, Loss=0.848]
+Epoch 298/10001:  60%|██████    | 6/10 [00:00<00:00, 16.62it/s, Loss=0.847]
+Epoch 298/10001:  60%|██████    | 6/10 [00:00<00:00, 16.62it/s, Loss=0.85] 
+Epoch 298/10001: 100%|██████████| 10/10 [00:00<00:00, 15.17it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 299/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 299/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 299/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.853]
+Epoch 299/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.853]
+Epoch 299/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.85] 
+Epoch 299/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.843]
+Epoch 299/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.843]
+Epoch 299/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.853]
+Epoch 299/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.855]
+Epoch 299/10001:  70%|███████   | 7/10 [00:00<00:00, 16.55it/s, Loss=0.855]
+Epoch 299/10001:  70%|███████   | 7/10 [00:00<00:00, 16.55it/s, Loss=0.852]
+Epoch 299/10001:  70%|███████   | 7/10 [00:00<00:00, 16.55it/s, Loss=0.849]
+Epoch 299/10001:  70%|███████   | 7/10 [00:00<00:00, 16.55it/s, Loss=0.855]
+Epoch 299/10001: 100%|██████████| 10/10 [00:00<00:00, 14.19it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 300/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 300/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 300/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.849]
+Epoch 300/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.851]
+Epoch 300/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.846]
+Epoch 300/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.855]
+Epoch 300/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.851]
+Epoch 300/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.851]
+Epoch 300/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.852]
+Epoch 300/10001:  10%|█         | 1/10 [00:00<00:02,  3.05it/s, Loss=0.846]
+Epoch 300/10001:  80%|████████  | 8/10 [00:00<00:00, 22.63it/s, Loss=0.846]
+Epoch 300/10001:  80%|████████  | 8/10 [00:00<00:00, 22.63it/s, Loss=0.855]
+Epoch 300/10001:  80%|████████  | 8/10 [00:00<00:00, 22.63it/s, Loss=0.846]
+Epoch 300/10001: 100%|██████████| 10/10 [00:00<00:00, 17.04it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 301/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 301/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 301/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.848]
+Epoch 301/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.847]
+Epoch 301/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.856]
+Epoch 301/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.852]
+Epoch 301/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.854]
+Epoch 301/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.854]
+Epoch 301/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.847]
+Epoch 301/10001:  70%|███████   | 7/10 [00:00<00:00, 14.98it/s, Loss=0.847]
+Epoch 301/10001:  70%|███████   | 7/10 [00:00<00:00, 14.98it/s, Loss=0.852]
+Epoch 301/10001:  70%|███████   | 7/10 [00:00<00:00, 14.98it/s, Loss=0.847]
+Epoch 301/10001:  70%|███████   | 7/10 [00:00<00:00, 14.98it/s, Loss=0.847]
+Epoch 301/10001: 100%|██████████| 10/10 [00:00<00:00, 13.00it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 302/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 302/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 302/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.843]
+Epoch 302/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.839]
+Epoch 302/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.858]
+Epoch 302/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.857]
+Epoch 302/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.856]
+Epoch 302/10001:  50%|█████     | 5/10 [00:00<00:00, 11.13it/s, Loss=0.856]
+Epoch 302/10001:  50%|█████     | 5/10 [00:00<00:00, 11.13it/s, Loss=0.858]
+Epoch 302/10001:  50%|█████     | 5/10 [00:00<00:00, 11.13it/s, Loss=0.847]
+Epoch 302/10001:  50%|█████     | 5/10 [00:00<00:00, 11.13it/s, Loss=0.848]
+Epoch 302/10001:  50%|█████     | 5/10 [00:00<00:00, 11.13it/s, Loss=0.844]
+Epoch 302/10001:  50%|█████     | 5/10 [00:00<00:00, 11.13it/s, Loss=0.859]
+Epoch 302/10001: 100%|██████████| 10/10 [00:00<00:00, 12.97it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 303/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 303/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 303/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.85]
+Epoch 303/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.852]
+Epoch 303/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.853]
+Epoch 303/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.86] 
+Epoch 303/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.853]
+Epoch 303/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.856]
+Epoch 303/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.846]
+Epoch 303/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.858]
+Epoch 303/10001:  80%|████████  | 8/10 [00:00<00:00, 18.78it/s, Loss=0.858]
+Epoch 303/10001:  80%|████████  | 8/10 [00:00<00:00, 18.78it/s, Loss=0.852]
+Epoch 303/10001:  80%|████████  | 8/10 [00:00<00:00, 18.78it/s, Loss=0.849]
+Epoch 303/10001: 100%|██████████| 10/10 [00:00<00:00, 14.45it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 304/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 304/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 304/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.852]
+Epoch 304/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.843]
+Epoch 304/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.849]
+Epoch 304/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.853]
+Epoch 304/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.856]
+Epoch 304/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.856]
+Epoch 304/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.854]
+Epoch 304/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.844]
+Epoch 304/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.845]
+Epoch 304/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.855]
+Epoch 304/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.86] 
+Epoch 304/10001: 100%|██████████| 10/10 [00:00<00:00, 20.47it/s, Loss=0.86]
+Epoch 304/10001: 100%|██████████| 10/10 [00:00<00:00, 12.68it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 305/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 305/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 305/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.848]
+Epoch 305/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.851]
+Epoch 305/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.851]
+Epoch 305/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.849]
+Epoch 305/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.851]
+Epoch 305/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.851]
+Epoch 305/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.848]
+Epoch 305/10001:  70%|███████   | 7/10 [00:00<00:00, 19.13it/s, Loss=0.848]
+Epoch 305/10001:  70%|███████   | 7/10 [00:00<00:00, 19.13it/s, Loss=0.85] 
+Epoch 305/10001:  70%|███████   | 7/10 [00:00<00:00, 19.13it/s, Loss=0.847]
+Epoch 305/10001:  70%|███████   | 7/10 [00:00<00:00, 19.13it/s, Loss=0.849]
+Epoch 305/10001: 100%|██████████| 10/10 [00:00<00:00, 15.66it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 306/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 306/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 306/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.853]
+Epoch 306/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.852]
+Epoch 306/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.846]
+Epoch 306/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.846]
+Epoch 306/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.846]
+Epoch 306/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.857]
+Epoch 306/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.852]
+Epoch 306/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.851]
+Epoch 306/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.85] 
+Epoch 306/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.849]
+Epoch 306/10001:  90%|█████████ | 9/10 [00:00<00:00, 22.01it/s, Loss=0.849]
+Epoch 306/10001:  90%|█████████ | 9/10 [00:00<00:00, 22.01it/s, Loss=0.849]
+Epoch 306/10001: 100%|██████████| 10/10 [00:00<00:00, 14.34it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 307/10001:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 307/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.848]
+Epoch 307/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.851]
+Epoch 307/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.841]
+Epoch 307/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.844]
+Epoch 307/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.852]
+Epoch 307/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.856]
+Epoch 307/10001:  60%|██████    | 6/10 [00:00<00:00, 13.36it/s, Loss=0.856]
+Epoch 307/10001:  60%|██████    | 6/10 [00:00<00:00, 13.36it/s, Loss=0.853]
+Epoch 307/10001:  60%|██████    | 6/10 [00:00<00:00, 13.36it/s, Loss=0.847]
+Epoch 307/10001:  60%|██████    | 6/10 [00:00<00:00, 13.36it/s, Loss=0.858]
+Epoch 307/10001:  60%|██████    | 6/10 [00:00<00:00, 13.36it/s, Loss=0.848]
+Epoch 307/10001: 100%|██████████| 10/10 [00:00<00:00, 12.83it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 308/10001:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 308/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.852]
+Epoch 308/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.861]
+Epoch 308/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.857]
+Epoch 308/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.857]
+Epoch 308/10001:  10%|█         | 1/10 [00:00<00:03,  2.81it/s, Loss=0.851]
+Epoch 308/10001:  50%|█████     | 5/10 [00:00<00:00, 12.55it/s, Loss=0.851]
+Epoch 308/10001:  50%|█████     | 5/10 [00:00<00:00, 12.55it/s, Loss=0.846]
+Epoch 308/10001:  50%|█████     | 5/10 [00:00<00:00, 12.55it/s, Loss=0.861]
+Epoch 308/10001:  50%|█████     | 5/10 [00:00<00:00, 12.55it/s, Loss=0.846]
+Epoch 308/10001:  50%|█████     | 5/10 [00:00<00:00, 12.55it/s, Loss=0.854]
+Epoch 308/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.02it/s, Loss=0.854]
+Epoch 308/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.02it/s, Loss=0.848]
+Epoch 308/10001: 100%|██████████| 10/10 [00:00<00:00, 12.95it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 309/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 309/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 309/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.848]
+Epoch 309/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.842]
+Epoch 309/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.857]
+Epoch 309/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.855]
+Epoch 309/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.844]
+Epoch 309/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.844]
+Epoch 309/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.854]
+Epoch 309/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.85] 
+Epoch 309/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.849]
+Epoch 309/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.851]
+Epoch 309/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.09it/s, Loss=0.851]
+Epoch 309/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.09it/s, Loss=0.852]
+Epoch 309/10001: 100%|██████████| 10/10 [00:00<00:00, 12.20it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 310/10001:   0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 310/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.851]
+Epoch 310/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.851]
+Epoch 310/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.846]
+Epoch 310/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.852]
+Epoch 310/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.852]
+Epoch 310/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.851]
+Epoch 310/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.851]
+Epoch 310/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.854]
+Epoch 310/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.854]
+Epoch 310/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.852]
+Epoch 310/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.851]
+Epoch 310/10001: 100%|██████████| 10/10 [00:00<00:00, 14.06it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 311/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 311/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 311/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.846]
+Epoch 311/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.855]
+Epoch 311/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.844]
+Epoch 311/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.853]
+Epoch 311/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.845]
+Epoch 311/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.858]
+Epoch 311/10001:  60%|██████    | 6/10 [00:00<00:00, 14.41it/s, Loss=0.858]
+Epoch 311/10001:  60%|██████    | 6/10 [00:00<00:00, 14.41it/s, Loss=0.843]
+Epoch 311/10001:  60%|██████    | 6/10 [00:00<00:00, 14.41it/s, Loss=0.852]
+Epoch 311/10001:  60%|██████    | 6/10 [00:00<00:00, 14.41it/s, Loss=0.856]
+Epoch 311/10001:  60%|██████    | 6/10 [00:00<00:00, 14.41it/s, Loss=0.851]
+Epoch 311/10001: 100%|██████████| 10/10 [00:00<00:00, 13.86it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 312/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 312/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 312/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.85]
+Epoch 312/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.855]
+Epoch 312/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.855]
+Epoch 312/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.85] 
+Epoch 312/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.848]
+Epoch 312/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.86] 
+Epoch 312/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.851]
+Epoch 312/10001:  70%|███████   | 7/10 [00:00<00:00, 18.60it/s, Loss=0.851]
+Epoch 312/10001:  70%|███████   | 7/10 [00:00<00:00, 18.60it/s, Loss=0.85] 
+Epoch 312/10001:  70%|███████   | 7/10 [00:00<00:00, 18.60it/s, Loss=0.845]
+Epoch 312/10001:  70%|███████   | 7/10 [00:00<00:00, 18.60it/s, Loss=0.853]
+Epoch 312/10001: 100%|██████████| 10/10 [00:00<00:00, 15.83it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 313/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 313/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 313/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.853]
+Epoch 313/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.857]
+Epoch 313/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.851]
+Epoch 313/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.845]
+Epoch 313/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.856]
+Epoch 313/10001:  50%|█████     | 5/10 [00:00<00:00, 12.71it/s, Loss=0.856]
+Epoch 313/10001:  50%|█████     | 5/10 [00:00<00:00, 12.71it/s, Loss=0.853]
+Epoch 313/10001:  50%|█████     | 5/10 [00:00<00:00, 12.71it/s, Loss=0.846]
+Epoch 313/10001:  50%|█████     | 5/10 [00:00<00:00, 12.71it/s, Loss=0.851]
+Epoch 313/10001:  50%|█████     | 5/10 [00:00<00:00, 12.71it/s, Loss=0.847]
+Epoch 313/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.81it/s, Loss=0.847]
+Epoch 313/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.81it/s, Loss=0.854]
+Epoch 313/10001: 100%|██████████| 10/10 [00:00<00:00, 13.74it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 314/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 314/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 314/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.849]
+Epoch 314/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.848]
+Epoch 314/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.853]
+Epoch 314/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.848]
+Epoch 314/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.85] 
+Epoch 314/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.848]
+Epoch 314/10001:  60%|██████    | 6/10 [00:00<00:00, 13.09it/s, Loss=0.848]
+Epoch 314/10001:  60%|██████    | 6/10 [00:00<00:00, 13.09it/s, Loss=0.849]
+Epoch 314/10001:  60%|██████    | 6/10 [00:00<00:00, 13.09it/s, Loss=0.849]
+Epoch 314/10001:  60%|██████    | 6/10 [00:00<00:00, 13.09it/s, Loss=0.857]
+Epoch 314/10001:  60%|██████    | 6/10 [00:00<00:00, 13.09it/s, Loss=0.855]
+Epoch 314/10001: 100%|██████████| 10/10 [00:00<00:00, 12.82it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 315/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 315/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 315/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.857]
+Epoch 315/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.851]
+Epoch 315/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.849]
+Epoch 315/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.853]
+Epoch 315/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.857]
+Epoch 315/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.84] 
+Epoch 315/10001:  60%|██████    | 6/10 [00:00<00:00, 15.98it/s, Loss=0.84]
+Epoch 315/10001:  60%|██████    | 6/10 [00:00<00:00, 15.98it/s, Loss=0.844]
+Epoch 315/10001:  60%|██████    | 6/10 [00:00<00:00, 15.98it/s, Loss=0.855]
+Epoch 315/10001:  60%|██████    | 6/10 [00:00<00:00, 15.98it/s, Loss=0.853]
+Epoch 315/10001:  60%|██████    | 6/10 [00:00<00:00, 15.98it/s, Loss=0.848]
+Epoch 315/10001: 100%|██████████| 10/10 [00:00<00:00, 15.56it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 316/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 316/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 316/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.856]
+Epoch 316/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.844]
+Epoch 316/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.852]
+Epoch 316/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.853]
+Epoch 316/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.856]
+Epoch 316/10001:  50%|█████     | 5/10 [00:00<00:00, 13.27it/s, Loss=0.856]
+Epoch 316/10001:  50%|█████     | 5/10 [00:00<00:00, 13.27it/s, Loss=0.852]
+Epoch 316/10001:  50%|█████     | 5/10 [00:00<00:00, 13.27it/s, Loss=0.859]
+Epoch 316/10001:  50%|█████     | 5/10 [00:00<00:00, 13.27it/s, Loss=0.848]
+Epoch 316/10001:  50%|█████     | 5/10 [00:00<00:00, 13.27it/s, Loss=0.85] 
+Epoch 316/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.33it/s, Loss=0.85]
+Epoch 316/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.33it/s, Loss=0.855]
+Epoch 316/10001: 100%|██████████| 10/10 [00:00<00:00, 14.03it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 317/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 317/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 317/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.851]
+Epoch 317/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.842]
+Epoch 317/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.853]
+Epoch 317/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.858]
+Epoch 317/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.851]
+Epoch 317/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.855]
+Epoch 317/10001:  60%|██████    | 6/10 [00:00<00:00, 15.10it/s, Loss=0.855]
+Epoch 317/10001:  60%|██████    | 6/10 [00:00<00:00, 15.10it/s, Loss=0.854]
+Epoch 317/10001:  60%|██████    | 6/10 [00:00<00:00, 15.10it/s, Loss=0.857]
+Epoch 317/10001:  60%|██████    | 6/10 [00:00<00:00, 15.10it/s, Loss=0.853]
+Epoch 317/10001:  60%|██████    | 6/10 [00:00<00:00, 15.10it/s, Loss=0.851]
+Epoch 317/10001: 100%|██████████| 10/10 [00:00<00:00, 14.39it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 318/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 318/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 318/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.849]
+Epoch 318/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.852]
+Epoch 318/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.85] 
+Epoch 318/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.845]
+Epoch 318/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.85] 
+Epoch 318/10001:  50%|█████     | 5/10 [00:00<00:00, 13.16it/s, Loss=0.85]
+Epoch 318/10001:  50%|█████     | 5/10 [00:00<00:00, 13.16it/s, Loss=0.849]
+Epoch 318/10001:  50%|█████     | 5/10 [00:00<00:00, 13.16it/s, Loss=0.853]
+Epoch 318/10001:  50%|█████     | 5/10 [00:00<00:00, 13.16it/s, Loss=0.853]
+Epoch 318/10001:  50%|█████     | 5/10 [00:00<00:00, 13.16it/s, Loss=0.85] 
+Epoch 318/10001:  50%|█████     | 5/10 [00:00<00:00, 13.16it/s, Loss=0.856]
+Epoch 318/10001: 100%|██████████| 10/10 [00:00<00:00, 15.13it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 319/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 319/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 319/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.85]
+Epoch 319/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.853]
+Epoch 319/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.848]
+Epoch 319/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.842]
+Epoch 319/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.853]
+Epoch 319/10001:  50%|█████     | 5/10 [00:00<00:00, 12.37it/s, Loss=0.853]
+Epoch 319/10001:  50%|█████     | 5/10 [00:00<00:00, 12.37it/s, Loss=0.854]
+Epoch 319/10001:  50%|█████     | 5/10 [00:00<00:00, 12.37it/s, Loss=0.85] 
+Epoch 319/10001:  50%|█████     | 5/10 [00:00<00:00, 12.37it/s, Loss=0.853]
+Epoch 319/10001:  50%|█████     | 5/10 [00:00<00:00, 12.37it/s, Loss=0.85] 
+Epoch 319/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.58it/s, Loss=0.85]
+Epoch 319/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.58it/s, Loss=0.857]
+Epoch 319/10001: 100%|██████████| 10/10 [00:00<00:00, 13.68it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 320/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 320/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 320/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.855]
+Epoch 320/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.848]
+Epoch 320/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.848]
+Epoch 320/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.851]
+Epoch 320/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.846]
+Epoch 320/10001:  10%|█         | 1/10 [00:00<00:03,  2.80it/s, Loss=0.844]
+Epoch 320/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.844]
+Epoch 320/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.845]
+Epoch 320/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.851]
+Epoch 320/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.854]
+Epoch 320/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.854]
+Epoch 320/10001: 100%|██████████| 10/10 [00:00<00:00, 15.69it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 321/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 321/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 321/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.85]
+Epoch 321/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.859]
+Epoch 321/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.842]
+Epoch 321/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.853]
+Epoch 321/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.851]
+Epoch 321/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.854]
+Epoch 321/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.85] 
+Epoch 321/10001:  70%|███████   | 7/10 [00:00<00:00, 15.69it/s, Loss=0.85]
+Epoch 321/10001:  70%|███████   | 7/10 [00:00<00:00, 15.69it/s, Loss=0.858]
+Epoch 321/10001:  70%|███████   | 7/10 [00:00<00:00, 15.69it/s, Loss=0.861]
+Epoch 321/10001:  70%|███████   | 7/10 [00:00<00:00, 15.69it/s, Loss=0.86] 
+Epoch 321/10001: 100%|██████████| 10/10 [00:00<00:00, 13.38it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 322/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 322/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 322/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.846]
+Epoch 322/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 322/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.847]
+Epoch 322/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.851]
+Epoch 322/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.857]
+Epoch 322/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 322/10001:  60%|██████    | 6/10 [00:00<00:00, 13.19it/s, Loss=0.853]
+Epoch 322/10001:  60%|██████    | 6/10 [00:00<00:00, 13.19it/s, Loss=0.858]
+Epoch 322/10001:  60%|██████    | 6/10 [00:00<00:00, 13.19it/s, Loss=0.847]
+Epoch 322/10001:  60%|██████    | 6/10 [00:00<00:00, 13.19it/s, Loss=0.855]
+Epoch 322/10001:  60%|██████    | 6/10 [00:00<00:00, 13.19it/s, Loss=0.853]
+Epoch 322/10001: 100%|██████████| 10/10 [00:00<00:00, 18.86it/s, Loss=0.853]
+Epoch 322/10001: 100%|██████████| 10/10 [00:00<00:00, 12.53it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 323/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 323/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 323/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.849]
+Epoch 323/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.852]
+Epoch 323/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.849]
+Epoch 323/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.85] 
+Epoch 323/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.855]
+Epoch 323/10001:  50%|█████     | 5/10 [00:00<00:00, 11.43it/s, Loss=0.855]
+Epoch 323/10001:  50%|█████     | 5/10 [00:00<00:00, 11.43it/s, Loss=0.853]
+Epoch 323/10001:  50%|█████     | 5/10 [00:00<00:00, 11.43it/s, Loss=0.85] 
+Epoch 323/10001:  50%|█████     | 5/10 [00:00<00:00, 11.43it/s, Loss=0.855]
+Epoch 323/10001:  50%|█████     | 5/10 [00:00<00:00, 11.43it/s, Loss=0.852]
+Epoch 323/10001:  50%|█████     | 5/10 [00:00<00:00, 11.43it/s, Loss=0.846]
+Epoch 323/10001: 100%|██████████| 10/10 [00:00<00:00, 13.47it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 324/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 324/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 324/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.856]
+Epoch 324/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.855]
+Epoch 324/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.852]
+Epoch 324/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.849]
+Epoch 324/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.853]
+Epoch 324/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.844]
+Epoch 324/10001:  60%|██████    | 6/10 [00:00<00:00, 15.50it/s, Loss=0.844]
+Epoch 324/10001:  60%|██████    | 6/10 [00:00<00:00, 15.50it/s, Loss=0.854]
+Epoch 324/10001:  60%|██████    | 6/10 [00:00<00:00, 15.50it/s, Loss=0.848]
+Epoch 324/10001:  60%|██████    | 6/10 [00:00<00:00, 15.50it/s, Loss=0.86] 
+Epoch 324/10001:  60%|██████    | 6/10 [00:00<00:00, 15.50it/s, Loss=0.85]
+Epoch 324/10001: 100%|██████████| 10/10 [00:00<00:00, 14.83it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 325/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 325/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 325/10001:  10%|█         | 1/10 [00:00<00:05,  1.63it/s, Loss=0.855]
+Epoch 325/10001:  10%|█         | 1/10 [00:00<00:05,  1.63it/s, Loss=0.857]
+Epoch 325/10001:  10%|█         | 1/10 [00:00<00:05,  1.63it/s, Loss=0.843]
+Epoch 325/10001:  10%|█         | 1/10 [00:00<00:05,  1.63it/s, Loss=0.854]
+Epoch 325/10001:  10%|█         | 1/10 [00:00<00:05,  1.63it/s, Loss=0.845]
+Epoch 325/10001:  50%|█████     | 5/10 [00:00<00:00,  8.70it/s, Loss=0.845]
+Epoch 325/10001:  50%|█████     | 5/10 [00:00<00:00,  8.70it/s, Loss=0.849]
+Epoch 325/10001:  50%|█████     | 5/10 [00:00<00:00,  8.70it/s, Loss=0.854]
+Epoch 325/10001:  50%|█████     | 5/10 [00:00<00:00,  8.70it/s, Loss=0.851]
+Epoch 325/10001:  50%|█████     | 5/10 [00:00<00:00,  8.70it/s, Loss=0.855]
+Epoch 325/10001:  90%|█████████ | 9/10 [00:00<00:00, 14.75it/s, Loss=0.855]
+Epoch 325/10001:  90%|█████████ | 9/10 [00:00<00:00, 14.75it/s, Loss=0.855]
+Epoch 325/10001: 100%|██████████| 10/10 [00:00<00:00, 10.06it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 326/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 326/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 326/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.855]
+Epoch 326/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.853]
+Epoch 326/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.852]
+Epoch 326/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.848]
+Epoch 326/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.854]
+Epoch 326/10001:  50%|█████     | 5/10 [00:00<00:00, 11.05it/s, Loss=0.854]
+Epoch 326/10001:  50%|█████     | 5/10 [00:00<00:00, 11.05it/s, Loss=0.849]
+Epoch 326/10001:  50%|█████     | 5/10 [00:00<00:00, 11.05it/s, Loss=0.854]
+Epoch 326/10001:  50%|█████     | 5/10 [00:00<00:00, 11.05it/s, Loss=0.85] 
+Epoch 326/10001:  50%|█████     | 5/10 [00:00<00:00, 11.05it/s, Loss=0.852]
+Epoch 326/10001:  50%|█████     | 5/10 [00:00<00:00, 11.05it/s, Loss=0.857]
+Epoch 326/10001: 100%|██████████| 10/10 [00:00<00:00, 13.24it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 327/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 327/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 327/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.849]
+Epoch 327/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.852]
+Epoch 327/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 327/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 327/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.847]
+Epoch 327/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.854]
+Epoch 327/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 327/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.858]
+Epoch 327/10001:  80%|████████  | 8/10 [00:00<00:00, 18.23it/s, Loss=0.858]
+Epoch 327/10001:  80%|████████  | 8/10 [00:00<00:00, 18.23it/s, Loss=0.853]
+Epoch 327/10001:  80%|████████  | 8/10 [00:00<00:00, 18.23it/s, Loss=0.853]
+Epoch 327/10001: 100%|██████████| 10/10 [00:00<00:00, 14.25it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 328/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 328/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 328/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.852]
+Epoch 328/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.851]
+Epoch 328/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.853]
+Epoch 328/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.845]
+Epoch 328/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.846]
+Epoch 328/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.85] 
+Epoch 328/10001:  60%|██████    | 6/10 [00:00<00:00, 14.25it/s, Loss=0.85]
+Epoch 328/10001:  60%|██████    | 6/10 [00:00<00:00, 14.25it/s, Loss=0.847]
+Epoch 328/10001:  60%|██████    | 6/10 [00:00<00:00, 14.25it/s, Loss=0.854]
+Epoch 328/10001:  60%|██████    | 6/10 [00:00<00:00, 14.25it/s, Loss=0.852]
+Epoch 328/10001:  60%|██████    | 6/10 [00:00<00:00, 14.25it/s, Loss=0.844]
+Epoch 328/10001: 100%|██████████| 10/10 [00:00<00:00, 14.11it/s, Loss=0.844]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 329/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 329/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 329/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.85]
+Epoch 329/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.848]
+Epoch 329/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.853]
+Epoch 329/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.854]
+Epoch 329/10001:  40%|████      | 4/10 [00:00<00:00,  8.62it/s, Loss=0.854]
+Epoch 329/10001:  40%|████      | 4/10 [00:00<00:00,  8.62it/s, Loss=0.853]
+Epoch 329/10001:  40%|████      | 4/10 [00:00<00:00,  8.62it/s, Loss=0.855]
+Epoch 329/10001:  40%|████      | 4/10 [00:00<00:00,  8.62it/s, Loss=0.85] 
+Epoch 329/10001:  40%|████      | 4/10 [00:00<00:00,  8.62it/s, Loss=0.843]
+Epoch 329/10001:  40%|████      | 4/10 [00:00<00:00,  8.62it/s, Loss=0.849]
+Epoch 329/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.91it/s, Loss=0.849]
+Epoch 329/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.91it/s, Loss=0.843]
+Epoch 329/10001: 100%|██████████| 10/10 [00:00<00:00, 12.46it/s, Loss=0.843]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 330/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 330/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 330/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.849]
+Epoch 330/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.858]
+Epoch 330/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.857]
+Epoch 330/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.848]
+Epoch 330/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.849]
+Epoch 330/10001:  10%|█         | 1/10 [00:00<00:03,  2.86it/s, Loss=0.857]
+Epoch 330/10001:  60%|██████    | 6/10 [00:00<00:00, 16.12it/s, Loss=0.857]
+Epoch 330/10001:  60%|██████    | 6/10 [00:00<00:00, 16.12it/s, Loss=0.852]
+Epoch 330/10001:  60%|██████    | 6/10 [00:00<00:00, 16.12it/s, Loss=0.857]
+Epoch 330/10001:  60%|██████    | 6/10 [00:00<00:00, 16.12it/s, Loss=0.853]
+Epoch 330/10001:  60%|██████    | 6/10 [00:00<00:00, 16.12it/s, Loss=0.853]
+Epoch 330/10001: 100%|██████████| 10/10 [00:00<00:00, 14.73it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 331/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 331/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 331/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.853]
+Epoch 331/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.855]
+Epoch 331/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.846]
+Epoch 331/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.851]
+Epoch 331/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.851]
+Epoch 331/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.855]
+Epoch 331/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.84] 
+Epoch 331/10001:  70%|███████   | 7/10 [00:00<00:00, 15.83it/s, Loss=0.84]
+Epoch 331/10001:  70%|███████   | 7/10 [00:00<00:00, 15.83it/s, Loss=0.847]
+Epoch 331/10001:  70%|███████   | 7/10 [00:00<00:00, 15.83it/s, Loss=0.85] 
+Epoch 331/10001:  70%|███████   | 7/10 [00:00<00:00, 15.83it/s, Loss=0.85]
+Epoch 331/10001: 100%|██████████| 10/10 [00:00<00:00, 13.47it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 332/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 332/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 332/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 332/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.849]
+Epoch 332/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.855]
+Epoch 332/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 332/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 332/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.854]
+Epoch 332/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.851]
+Epoch 332/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.853]
+Epoch 332/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.85] 
+Epoch 332/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.847]
+Epoch 332/10001:  50%|█████     | 5/10 [00:00<00:00, 10.86it/s, Loss=0.854]
+Epoch 332/10001: 100%|██████████| 10/10 [00:00<00:00, 20.17it/s, Loss=0.854]
+Epoch 332/10001: 100%|██████████| 10/10 [00:00<00:00, 12.78it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 333/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 333/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 333/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.854]
+Epoch 333/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.847]
+Epoch 333/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.852]
+Epoch 333/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.848]
+Epoch 333/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.845]
+Epoch 333/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.855]
+Epoch 333/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.855]
+Epoch 333/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.851]
+Epoch 333/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.86] 
+Epoch 333/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.847]
+Epoch 333/10001:  60%|██████    | 6/10 [00:00<00:00, 13.90it/s, Loss=0.857]
+Epoch 333/10001: 100%|██████████| 10/10 [00:00<00:00, 20.34it/s, Loss=0.857]
+Epoch 333/10001: 100%|██████████| 10/10 [00:00<00:00, 13.36it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 334/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 334/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 334/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.858]
+Epoch 334/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.859]
+Epoch 334/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.857]
+Epoch 334/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.848]
+Epoch 334/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.854]
+Epoch 334/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.845]
+Epoch 334/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.857]
+Epoch 334/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.845]
+Epoch 334/10001:  80%|████████  | 8/10 [00:00<00:00, 17.97it/s, Loss=0.845]
+Epoch 334/10001:  80%|████████  | 8/10 [00:00<00:00, 17.97it/s, Loss=0.845]
+Epoch 334/10001:  80%|████████  | 8/10 [00:00<00:00, 17.97it/s, Loss=0.857]
+Epoch 334/10001: 100%|██████████| 10/10 [00:00<00:00, 13.33it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 335/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 335/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 335/10001:  10%|█         | 1/10 [00:00<00:04,  1.88it/s, Loss=0.847]
+Epoch 335/10001:  10%|█         | 1/10 [00:00<00:04,  1.88it/s, Loss=0.851]
+Epoch 335/10001:  10%|█         | 1/10 [00:00<00:04,  1.88it/s, Loss=0.855]
+Epoch 335/10001:  10%|█         | 1/10 [00:00<00:04,  1.88it/s, Loss=0.853]
+Epoch 335/10001:  10%|█         | 1/10 [00:00<00:04,  1.88it/s, Loss=0.856]
+Epoch 335/10001:  10%|█         | 1/10 [00:00<00:04,  1.88it/s, Loss=0.854]
+Epoch 335/10001:  10%|█         | 1/10 [00:00<00:04,  1.88it/s, Loss=0.849]
+Epoch 335/10001:  70%|███████   | 7/10 [00:00<00:00, 13.94it/s, Loss=0.849]
+Epoch 335/10001:  70%|███████   | 7/10 [00:00<00:00, 13.94it/s, Loss=0.85] 
+Epoch 335/10001:  70%|███████   | 7/10 [00:00<00:00, 13.94it/s, Loss=0.851]
+Epoch 335/10001:  70%|███████   | 7/10 [00:00<00:00, 13.94it/s, Loss=0.859]
+Epoch 335/10001: 100%|██████████| 10/10 [00:00<00:00, 12.61it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 336/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 336/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 336/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.845]
+Epoch 336/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.849]
+Epoch 336/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.853]
+Epoch 336/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.852]
+Epoch 336/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.849]
+Epoch 336/10001:  50%|█████     | 5/10 [00:00<00:00, 10.96it/s, Loss=0.849]
+Epoch 336/10001:  50%|█████     | 5/10 [00:00<00:00, 10.96it/s, Loss=0.848]
+Epoch 336/10001:  50%|█████     | 5/10 [00:00<00:00, 10.96it/s, Loss=0.849]
+Epoch 336/10001:  50%|█████     | 5/10 [00:00<00:00, 10.96it/s, Loss=0.856]
+Epoch 336/10001:  50%|█████     | 5/10 [00:00<00:00, 10.96it/s, Loss=0.853]
+Epoch 336/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.55it/s, Loss=0.853]
+Epoch 336/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.55it/s, Loss=0.849]
+Epoch 336/10001: 100%|██████████| 10/10 [00:00<00:00, 12.35it/s, Loss=0.849]
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+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 337/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 337/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 337/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.856]
+Epoch 337/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.851]
+Epoch 337/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.854]
+Epoch 337/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.847]
+Epoch 337/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.853]
+Epoch 337/10001:  50%|█████     | 5/10 [00:00<00:00, 12.35it/s, Loss=0.853]
+Epoch 337/10001:  50%|█████     | 5/10 [00:00<00:00, 12.35it/s, Loss=0.854]
+Epoch 337/10001:  50%|█████     | 5/10 [00:00<00:00, 12.35it/s, Loss=0.848]
+Epoch 337/10001:  50%|█████     | 5/10 [00:00<00:00, 12.35it/s, Loss=0.854]
+Epoch 337/10001:  50%|█████     | 5/10 [00:00<00:00, 12.35it/s, Loss=0.851]
+Epoch 337/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.14it/s, Loss=0.851]
+Epoch 337/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.14it/s, Loss=0.854]
+Epoch 337/10001: 100%|██████████| 10/10 [00:00<00:00, 12.82it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 338/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 338/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.86]
+Epoch 338/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.86]
+Epoch 338/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.854]
+Epoch 338/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.852]
+Epoch 338/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.854]
+Epoch 338/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.847]
+Epoch 338/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.854]
+Epoch 338/10001:  60%|██████    | 6/10 [00:00<00:00, 13.41it/s, Loss=0.854]
+Epoch 338/10001:  60%|██████    | 6/10 [00:00<00:00, 13.41it/s, Loss=0.856]
+Epoch 338/10001:  60%|██████    | 6/10 [00:00<00:00, 13.41it/s, Loss=0.86] 
+Epoch 338/10001:  60%|██████    | 6/10 [00:00<00:00, 13.41it/s, Loss=0.855]
+Epoch 338/10001:  60%|██████    | 6/10 [00:00<00:00, 13.41it/s, Loss=0.846]
+Epoch 338/10001: 100%|██████████| 10/10 [00:00<00:00, 13.16it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 339/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 339/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 339/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.855]
+Epoch 339/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.852]
+Epoch 339/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.853]
+Epoch 339/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.845]
+Epoch 339/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.859]
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+Epoch 339/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.854]
+Epoch 339/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.854]
+Epoch 339/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.843]
+Epoch 339/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.855]
+Epoch 339/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.854]
+Epoch 339/10001: 100%|██████████| 10/10 [00:00<00:00, 19.16it/s, Loss=0.854]
+Epoch 339/10001: 100%|██████████| 10/10 [00:00<00:00, 11.42it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 340/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 340/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 340/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.857]
+Epoch 340/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.85] 
+Epoch 340/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.849]
+Epoch 340/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.854]
+Epoch 340/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.849]
+Epoch 340/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.848]
+Epoch 340/10001:  60%|██████    | 6/10 [00:00<00:00, 12.98it/s, Loss=0.848]
+Epoch 340/10001:  60%|██████    | 6/10 [00:00<00:00, 12.98it/s, Loss=0.849]
+Epoch 340/10001:  60%|██████    | 6/10 [00:00<00:00, 12.98it/s, Loss=0.852]
+Epoch 340/10001:  60%|██████    | 6/10 [00:00<00:00, 12.98it/s, Loss=0.851]
+Epoch 340/10001:  60%|██████    | 6/10 [00:00<00:00, 12.98it/s, Loss=0.845]
+Epoch 340/10001: 100%|██████████| 10/10 [00:00<00:00, 19.27it/s, Loss=0.845]
+Epoch 340/10001: 100%|██████████| 10/10 [00:00<00:00, 12.16it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 341/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 341/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 341/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.851]
+Epoch 341/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.844]
+Epoch 341/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.851]
+Epoch 341/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.847]
+Epoch 341/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.854]
+Epoch 341/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.858]
+Epoch 341/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.858]
+Epoch 341/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.856]
+Epoch 341/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.856]
+Epoch 341/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.858]
+Epoch 341/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.843]
+Epoch 341/10001: 100%|██████████| 10/10 [00:00<00:00, 13.44it/s, Loss=0.843]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 342/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 342/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 342/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 342/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.844]
+Epoch 342/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.846]
+Epoch 342/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.85] 
+Epoch 342/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.855]
+Epoch 342/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.849]
+Epoch 342/10001:  60%|██████    | 6/10 [00:00<00:00, 13.66it/s, Loss=0.849]
+Epoch 342/10001:  60%|██████    | 6/10 [00:00<00:00, 13.66it/s, Loss=0.851]
+Epoch 342/10001:  60%|██████    | 6/10 [00:00<00:00, 13.66it/s, Loss=0.856]
+Epoch 342/10001:  60%|██████    | 6/10 [00:00<00:00, 13.66it/s, Loss=0.85] 
+Epoch 342/10001:  60%|██████    | 6/10 [00:00<00:00, 13.66it/s, Loss=0.855]
+Epoch 342/10001: 100%|██████████| 10/10 [00:00<00:00, 12.77it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 343/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 343/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 343/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.853]
+Epoch 343/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.852]
+Epoch 343/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.85] 
+Epoch 343/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.853]
+Epoch 343/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.847]
+Epoch 343/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.852]
+Epoch 343/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.855]
+Epoch 343/10001:  70%|███████   | 7/10 [00:00<00:00, 16.04it/s, Loss=0.855]
+Epoch 343/10001:  70%|███████   | 7/10 [00:00<00:00, 16.04it/s, Loss=0.85] 
+Epoch 343/10001:  70%|███████   | 7/10 [00:00<00:00, 16.04it/s, Loss=0.854]
+Epoch 343/10001:  70%|███████   | 7/10 [00:00<00:00, 16.04it/s, Loss=0.849]
+Epoch 343/10001: 100%|██████████| 10/10 [00:00<00:00, 13.64it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 344/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 344/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.844]
+Epoch 344/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.844]
+Epoch 344/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.853]
+Epoch 344/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.847]
+Epoch 344/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.85] 
+Epoch 344/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.85]
+Epoch 344/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.85]
+Epoch 344/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.851]
+Epoch 344/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.844]
+Epoch 344/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.85] 
+Epoch 344/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.854]
+Epoch 344/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.87it/s, Loss=0.854]
+Epoch 344/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.87it/s, Loss=0.86] 
+Epoch 344/10001: 100%|██████████| 10/10 [00:00<00:00, 13.08it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 345/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 345/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 345/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.849]
+Epoch 345/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.856]
+Epoch 345/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.852]
+Epoch 345/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.858]
+Epoch 345/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.846]
+Epoch 345/10001:  10%|█         | 1/10 [00:00<00:04,  2.13it/s, Loss=0.854]
+Epoch 345/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.854]
+Epoch 345/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.843]
+Epoch 345/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.849]
+Epoch 345/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.853]
+Epoch 345/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.855]
+Epoch 345/10001: 100%|██████████| 10/10 [00:00<00:00, 13.24it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 346/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 346/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 346/10001:  10%|█         | 1/10 [00:00<00:04,  2.03it/s, Loss=0.853]
+Epoch 346/10001:  10%|█         | 1/10 [00:00<00:04,  2.03it/s, Loss=0.851]
+Epoch 346/10001:  10%|█         | 1/10 [00:00<00:04,  2.03it/s, Loss=0.849]
+Epoch 346/10001:  10%|█         | 1/10 [00:00<00:04,  2.03it/s, Loss=0.847]
+Epoch 346/10001:  10%|█         | 1/10 [00:00<00:04,  2.03it/s, Loss=0.854]
+Epoch 346/10001:  10%|█         | 1/10 [00:00<00:04,  2.03it/s, Loss=0.857]
+Epoch 346/10001:  10%|█         | 1/10 [00:00<00:04,  2.03it/s, Loss=0.853]
+Epoch 346/10001:  70%|███████   | 7/10 [00:00<00:00, 14.92it/s, Loss=0.853]
+Epoch 346/10001:  70%|███████   | 7/10 [00:00<00:00, 14.92it/s, Loss=0.851]
+Epoch 346/10001:  70%|███████   | 7/10 [00:00<00:00, 14.92it/s, Loss=0.85] 
+Epoch 346/10001:  70%|███████   | 7/10 [00:00<00:00, 14.92it/s, Loss=0.842]
+Epoch 346/10001: 100%|██████████| 10/10 [00:00<00:00, 12.76it/s, Loss=0.842]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 347/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 347/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 347/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.853]
+Epoch 347/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.854]
+Epoch 347/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.852]
+Epoch 347/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.855]
+Epoch 347/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.861]
+Epoch 347/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.861]
+Epoch 347/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.846]
+Epoch 347/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.852]
+Epoch 347/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.847]
+Epoch 347/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.844]
+Epoch 347/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.854]
+Epoch 347/10001: 100%|██████████| 10/10 [00:00<00:00, 21.45it/s, Loss=0.854]
+Epoch 347/10001: 100%|██████████| 10/10 [00:00<00:00, 13.57it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 348/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 348/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.859]
+Epoch 348/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.859]
+Epoch 348/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.851]
+Epoch 348/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.848]
+Epoch 348/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.857]
+Epoch 348/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.862]
+Epoch 348/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.86] 
+Epoch 348/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.849]
+Epoch 348/10001:  70%|███████   | 7/10 [00:00<00:00, 17.90it/s, Loss=0.849]
+Epoch 348/10001:  70%|███████   | 7/10 [00:00<00:00, 17.90it/s, Loss=0.856]
+Epoch 348/10001:  70%|███████   | 7/10 [00:00<00:00, 17.90it/s, Loss=0.861]
+Epoch 348/10001:  70%|███████   | 7/10 [00:00<00:00, 17.90it/s, Loss=0.85] 
+Epoch 348/10001: 100%|██████████| 10/10 [00:00<00:00, 15.38it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 349/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 349/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 349/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.852]
+Epoch 349/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.843]
+Epoch 349/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.853]
+Epoch 349/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.85] 
+Epoch 349/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.856]
+Epoch 349/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.845]
+Epoch 349/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.848]
+Epoch 349/10001:  70%|███████   | 7/10 [00:00<00:00, 16.69it/s, Loss=0.848]
+Epoch 349/10001:  70%|███████   | 7/10 [00:00<00:00, 16.69it/s, Loss=0.85] 
+Epoch 349/10001:  70%|███████   | 7/10 [00:00<00:00, 16.69it/s, Loss=0.85]
+Epoch 349/10001:  70%|███████   | 7/10 [00:00<00:00, 16.69it/s, Loss=0.858]
+Epoch 349/10001: 100%|██████████| 10/10 [00:00<00:00, 14.09it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 350/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 350/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 350/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.85]
+Epoch 350/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.864]
+Epoch 350/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.854]
+Epoch 350/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.854]
+Epoch 350/10001:  40%|████      | 4/10 [00:00<00:00,  8.54it/s, Loss=0.854]
+Epoch 350/10001:  40%|████      | 4/10 [00:00<00:00,  8.54it/s, Loss=0.851]
+Epoch 350/10001:  40%|████      | 4/10 [00:00<00:00,  8.54it/s, Loss=0.849]
+Epoch 350/10001:  40%|████      | 4/10 [00:00<00:00,  8.54it/s, Loss=0.845]
+Epoch 350/10001:  40%|████      | 4/10 [00:00<00:00,  8.54it/s, Loss=0.852]
+Epoch 350/10001:  80%|████████  | 8/10 [00:00<00:00, 16.10it/s, Loss=0.852]
+Epoch 350/10001:  80%|████████  | 8/10 [00:00<00:00, 16.10it/s, Loss=0.855]
+Epoch 350/10001:  80%|████████  | 8/10 [00:00<00:00, 16.10it/s, Loss=0.851]
+Epoch 350/10001: 100%|██████████| 10/10 [00:00<00:00, 11.63it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 351/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 351/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.838]
+Epoch 351/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.838]
+Epoch 351/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.85] 
+Epoch 351/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.849]
+Epoch 351/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.846]
+Epoch 351/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.859]
+Epoch 351/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.849]
+Epoch 351/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.855]
+Epoch 351/10001:  70%|███████   | 7/10 [00:00<00:00, 15.42it/s, Loss=0.855]
+Epoch 351/10001:  70%|███████   | 7/10 [00:00<00:00, 15.42it/s, Loss=0.849]
+Epoch 351/10001:  70%|███████   | 7/10 [00:00<00:00, 15.42it/s, Loss=0.856]
+Epoch 351/10001:  70%|███████   | 7/10 [00:00<00:00, 15.42it/s, Loss=0.86] 
+Epoch 351/10001: 100%|██████████| 10/10 [00:00<00:00, 13.67it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 352/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 352/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 352/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.854]
+Epoch 352/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.852]
+Epoch 352/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.842]
+Epoch 352/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.852]
+Epoch 352/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.849]
+Epoch 352/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.862]
+Epoch 352/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.862]
+Epoch 352/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.849]
+Epoch 352/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.853]
+Epoch 352/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.855]
+Epoch 352/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.846]
+Epoch 352/10001: 100%|██████████| 10/10 [00:00<00:00, 13.61it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 353/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 353/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 353/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.848]
+Epoch 353/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.841]
+Epoch 353/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.854]
+Epoch 353/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.85] 
+Epoch 353/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.847]
+Epoch 353/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.844]
+Epoch 353/10001:  60%|██████    | 6/10 [00:00<00:00, 13.51it/s, Loss=0.844]
+Epoch 353/10001:  60%|██████    | 6/10 [00:00<00:00, 13.51it/s, Loss=0.846]
+Epoch 353/10001:  60%|██████    | 6/10 [00:00<00:00, 13.51it/s, Loss=0.848]
+Epoch 353/10001:  60%|██████    | 6/10 [00:00<00:00, 13.51it/s, Loss=0.862]
+Epoch 353/10001:  60%|██████    | 6/10 [00:00<00:00, 13.51it/s, Loss=0.849]
+Epoch 353/10001: 100%|██████████| 10/10 [00:00<00:00, 13.56it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 354/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 354/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.862]
+Epoch 354/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.862]
+Epoch 354/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.848]
+Epoch 354/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.854]
+Epoch 354/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.851]
+Epoch 354/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.848]
+Epoch 354/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.853]
+Epoch 354/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.853]
+Epoch 354/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.856]
+Epoch 354/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.844]
+Epoch 354/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.846]
+Epoch 354/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.849]
+Epoch 354/10001: 100%|██████████| 10/10 [00:00<00:00, 13.40it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 355/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 355/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.841]
+Epoch 355/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.841]
+Epoch 355/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.849]
+Epoch 355/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.853]
+Epoch 355/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.854]
+Epoch 355/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.848]
+Epoch 355/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.858]
+Epoch 355/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.858]
+Epoch 355/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.856]
+Epoch 355/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.855]
+Epoch 355/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.862]
+Epoch 355/10001:  60%|██████    | 6/10 [00:00<00:00, 14.12it/s, Loss=0.856]
+Epoch 355/10001: 100%|██████████| 10/10 [00:00<00:00, 13.81it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 356/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 356/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 356/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.851]
+Epoch 356/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.839]
+Epoch 356/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.854]
+Epoch 356/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.845]
+Epoch 356/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 356/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.853]
+Epoch 356/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.847]
+Epoch 356/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.844]
+Epoch 356/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.852]
+Epoch 356/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.854]
+Epoch 356/10001:  50%|█████     | 5/10 [00:00<00:00, 11.22it/s, Loss=0.849]
+Epoch 356/10001: 100%|██████████| 10/10 [00:00<00:00, 20.63it/s, Loss=0.849]
+Epoch 356/10001: 100%|██████████| 10/10 [00:00<00:00, 13.06it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 357/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 357/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.844]
+Epoch 357/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.844]
+Epoch 357/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.848]
+Epoch 357/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.855]
+Epoch 357/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.851]
+Epoch 357/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.856]
+Epoch 357/10001:  50%|█████     | 5/10 [00:00<00:00, 11.52it/s, Loss=0.856]
+Epoch 357/10001:  50%|█████     | 5/10 [00:00<00:00, 11.52it/s, Loss=0.848]
+Epoch 357/10001:  50%|█████     | 5/10 [00:00<00:00, 11.52it/s, Loss=0.851]
+Epoch 357/10001:  50%|█████     | 5/10 [00:00<00:00, 11.52it/s, Loss=0.858]
+Epoch 357/10001:  50%|█████     | 5/10 [00:00<00:00, 11.52it/s, Loss=0.859]
+Epoch 357/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.53it/s, Loss=0.859]
+Epoch 357/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.53it/s, Loss=0.845]
+Epoch 357/10001: 100%|██████████| 10/10 [00:00<00:00, 12.98it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 358/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 358/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 358/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.856]
+Epoch 358/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.85] 
+Epoch 358/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.852]
+Epoch 358/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.853]
+Epoch 358/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.847]
+Epoch 358/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 358/10001:  60%|██████    | 6/10 [00:00<00:00, 13.71it/s, Loss=0.854]
+Epoch 358/10001:  60%|██████    | 6/10 [00:00<00:00, 13.71it/s, Loss=0.853]
+Epoch 358/10001:  60%|██████    | 6/10 [00:00<00:00, 13.71it/s, Loss=0.846]
+Epoch 358/10001:  60%|██████    | 6/10 [00:00<00:00, 13.71it/s, Loss=0.852]
+Epoch 358/10001:  60%|██████    | 6/10 [00:00<00:00, 13.71it/s, Loss=0.848]
+Epoch 358/10001: 100%|██████████| 10/10 [00:00<00:00, 19.81it/s, Loss=0.848]
+Epoch 358/10001: 100%|██████████| 10/10 [00:00<00:00, 13.12it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 359/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 359/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 359/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.855]
+Epoch 359/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.853]
+Epoch 359/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.852]
+Epoch 359/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.85] 
+Epoch 359/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.851]
+Epoch 359/10001:  50%|█████     | 5/10 [00:00<00:00, 10.33it/s, Loss=0.851]
+Epoch 359/10001:  50%|█████     | 5/10 [00:00<00:00, 10.33it/s, Loss=0.856]
+Epoch 359/10001:  50%|█████     | 5/10 [00:00<00:00, 10.33it/s, Loss=0.853]
+Epoch 359/10001:  50%|█████     | 5/10 [00:00<00:00, 10.33it/s, Loss=0.847]
+Epoch 359/10001:  50%|█████     | 5/10 [00:00<00:00, 10.33it/s, Loss=0.853]
+Epoch 359/10001:  90%|█████████ | 9/10 [00:00<00:00, 16.86it/s, Loss=0.853]
+Epoch 359/10001:  90%|█████████ | 9/10 [00:00<00:00, 16.86it/s, Loss=0.854]
+Epoch 359/10001: 100%|██████████| 10/10 [00:00<00:00, 11.73it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 360/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 360/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 360/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.858]
+Epoch 360/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.848]
+Epoch 360/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.85] 
+Epoch 360/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.855]
+Epoch 360/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.847]
+Epoch 360/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.853]
+Epoch 360/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.857]
+Epoch 360/10001:  70%|███████   | 7/10 [00:00<00:00, 15.93it/s, Loss=0.857]
+Epoch 360/10001:  70%|███████   | 7/10 [00:00<00:00, 15.93it/s, Loss=0.851]
+Epoch 360/10001:  70%|███████   | 7/10 [00:00<00:00, 15.93it/s, Loss=0.85] 
+Epoch 360/10001:  70%|███████   | 7/10 [00:00<00:00, 15.93it/s, Loss=0.852]
+Epoch 360/10001: 100%|██████████| 10/10 [00:00<00:00, 13.73it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 361/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 361/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 361/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.849]
+Epoch 361/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.847]
+Epoch 361/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.856]
+Epoch 361/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.854]
+Epoch 361/10001:  10%|█         | 1/10 [00:00<00:03,  2.25it/s, Loss=0.847]
+Epoch 361/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.847]
+Epoch 361/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.856]
+Epoch 361/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.857]
+Epoch 361/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.846]
+Epoch 361/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.852]
+Epoch 361/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.85] 
+Epoch 361/10001: 100%|██████████| 10/10 [00:00<00:00, 20.32it/s, Loss=0.85]
+Epoch 361/10001: 100%|██████████| 10/10 [00:00<00:00, 12.83it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 362/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 362/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.838]
+Epoch 362/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.838]
+Epoch 362/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.856]
+Epoch 362/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.845]
+Epoch 362/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.856]
+Epoch 362/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.856]
+Epoch 362/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.855]
+Epoch 362/10001:  60%|██████    | 6/10 [00:00<00:00, 13.83it/s, Loss=0.855]
+Epoch 362/10001:  60%|██████    | 6/10 [00:00<00:00, 13.83it/s, Loss=0.857]
+Epoch 362/10001:  60%|██████    | 6/10 [00:00<00:00, 13.83it/s, Loss=0.85] 
+Epoch 362/10001:  60%|██████    | 6/10 [00:00<00:00, 13.83it/s, Loss=0.85]
+Epoch 362/10001:  60%|██████    | 6/10 [00:00<00:00, 13.83it/s, Loss=0.847]
+Epoch 362/10001: 100%|██████████| 10/10 [00:00<00:00, 14.00it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 363/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 363/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 363/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.851]
+Epoch 363/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.856]
+Epoch 363/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.852]
+Epoch 363/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.849]
+Epoch 363/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.847]
+Epoch 363/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.843]
+Epoch 363/10001:  60%|██████    | 6/10 [00:00<00:00, 13.79it/s, Loss=0.843]
+Epoch 363/10001:  60%|██████    | 6/10 [00:00<00:00, 13.79it/s, Loss=0.853]
+Epoch 363/10001:  60%|██████    | 6/10 [00:00<00:00, 13.79it/s, Loss=0.851]
+Epoch 363/10001:  60%|██████    | 6/10 [00:00<00:00, 13.79it/s, Loss=0.851]
+Epoch 363/10001:  60%|██████    | 6/10 [00:00<00:00, 13.79it/s, Loss=0.85] 
+Epoch 363/10001: 100%|██████████| 10/10 [00:00<00:00, 14.00it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 364/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 364/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 364/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.852]
+Epoch 364/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.849]
+Epoch 364/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.856]
+Epoch 364/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.85] 
+Epoch 364/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.851]
+Epoch 364/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.851]
+Epoch 364/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.848]
+Epoch 364/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.848]
+Epoch 364/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.849]
+Epoch 364/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.855]
+Epoch 364/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.91it/s, Loss=0.855]
+Epoch 364/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.91it/s, Loss=0.843]
+Epoch 364/10001: 100%|██████████| 10/10 [00:00<00:00, 12.42it/s, Loss=0.843]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 365/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 365/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 365/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.846]
+Epoch 365/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.853]
+Epoch 365/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.852]
+Epoch 365/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.849]
+Epoch 365/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.85] 
+Epoch 365/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.85]
+Epoch 365/10001:  60%|██████    | 6/10 [00:00<00:00, 14.39it/s, Loss=0.85]
+Epoch 365/10001:  60%|██████    | 6/10 [00:00<00:00, 14.39it/s, Loss=0.848]
+Epoch 365/10001:  60%|██████    | 6/10 [00:00<00:00, 14.39it/s, Loss=0.854]
+Epoch 365/10001:  60%|██████    | 6/10 [00:00<00:00, 14.39it/s, Loss=0.849]
+Epoch 365/10001:  60%|██████    | 6/10 [00:00<00:00, 14.39it/s, Loss=0.851]
+Epoch 365/10001: 100%|██████████| 10/10 [00:00<00:00, 14.09it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 366/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 366/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.84]
+Epoch 366/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.84]
+Epoch 366/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.855]
+Epoch 366/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.86] 
+Epoch 366/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.857]
+Epoch 366/10001:  40%|████      | 4/10 [00:00<00:00,  9.10it/s, Loss=0.857]
+Epoch 366/10001:  40%|████      | 4/10 [00:00<00:00,  9.10it/s, Loss=0.853]
+Epoch 366/10001:  40%|████      | 4/10 [00:00<00:00,  9.10it/s, Loss=0.854]
+Epoch 366/10001:  40%|████      | 4/10 [00:00<00:00,  9.10it/s, Loss=0.846]
+Epoch 366/10001:  40%|████      | 4/10 [00:00<00:00,  9.10it/s, Loss=0.851]
+Epoch 366/10001:  40%|████      | 4/10 [00:00<00:00,  9.10it/s, Loss=0.845]
+Epoch 366/10001:  40%|████      | 4/10 [00:00<00:00,  9.10it/s, Loss=0.859]
+Epoch 366/10001: 100%|██████████| 10/10 [00:00<00:00, 22.28it/s, Loss=0.859]
+Epoch 366/10001: 100%|██████████| 10/10 [00:00<00:00, 12.77it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 367/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 367/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 367/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.853]
+Epoch 367/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.85] 
+Epoch 367/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.85]
+Epoch 367/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.845]
+Epoch 367/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.848]
+Epoch 367/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.849]
+Epoch 367/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.849]
+Epoch 367/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.854]
+Epoch 367/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.847]
+Epoch 367/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.844]
+Epoch 367/10001:  60%|██████    | 6/10 [00:00<00:00, 14.17it/s, Loss=0.856]
+Epoch 367/10001: 100%|██████████| 10/10 [00:00<00:00, 14.16it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 368/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 368/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 368/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.849]
+Epoch 368/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.849]
+Epoch 368/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.839]
+Epoch 368/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.843]
+Epoch 368/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.846]
+Epoch 368/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.855]
+Epoch 368/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.853]
+Epoch 368/10001:  70%|███████   | 7/10 [00:00<00:00, 16.18it/s, Loss=0.853]
+Epoch 368/10001:  70%|███████   | 7/10 [00:00<00:00, 16.18it/s, Loss=0.855]
+Epoch 368/10001:  70%|███████   | 7/10 [00:00<00:00, 16.18it/s, Loss=0.843]
+Epoch 368/10001:  70%|███████   | 7/10 [00:00<00:00, 16.18it/s, Loss=0.847]
+Epoch 368/10001: 100%|██████████| 10/10 [00:00<00:00, 14.18it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 369/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 369/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 369/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.85]
+Epoch 369/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.85]
+Epoch 369/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.849]
+Epoch 369/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.849]
+Epoch 369/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.852]
+Epoch 369/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.852]
+Epoch 369/10001:  60%|██████    | 6/10 [00:00<00:00, 13.77it/s, Loss=0.852]
+Epoch 369/10001:  60%|██████    | 6/10 [00:00<00:00, 13.77it/s, Loss=0.856]
+Epoch 369/10001:  60%|██████    | 6/10 [00:00<00:00, 13.77it/s, Loss=0.851]
+Epoch 369/10001:  60%|██████    | 6/10 [00:00<00:00, 13.77it/s, Loss=0.854]
+Epoch 369/10001:  60%|██████    | 6/10 [00:00<00:00, 13.77it/s, Loss=0.852]
+Epoch 369/10001: 100%|██████████| 10/10 [00:00<00:00, 13.75it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 370/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 370/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 370/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.855]
+Epoch 370/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.848]
+Epoch 370/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.85] 
+Epoch 370/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.857]
+Epoch 370/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.853]
+Epoch 370/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.846]
+Epoch 370/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.845]
+Epoch 370/10001:  70%|███████   | 7/10 [00:00<00:00, 18.59it/s, Loss=0.845]
+Epoch 370/10001:  70%|███████   | 7/10 [00:00<00:00, 18.59it/s, Loss=0.86] 
+Epoch 370/10001:  70%|███████   | 7/10 [00:00<00:00, 18.59it/s, Loss=0.854]
+Epoch 370/10001:  70%|███████   | 7/10 [00:00<00:00, 18.59it/s, Loss=0.845]
+Epoch 370/10001: 100%|██████████| 10/10 [00:00<00:00, 16.07it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 371/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 371/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 371/10001:  10%|█         | 1/10 [00:00<00:04,  1.84it/s, Loss=0.853]
+Epoch 371/10001:  10%|█         | 1/10 [00:00<00:04,  1.84it/s, Loss=0.858]
+Epoch 371/10001:  10%|█         | 1/10 [00:00<00:04,  1.84it/s, Loss=0.85] 
+Epoch 371/10001:  10%|█         | 1/10 [00:00<00:04,  1.84it/s, Loss=0.851]
+Epoch 371/10001:  10%|█         | 1/10 [00:00<00:04,  1.84it/s, Loss=0.852]
+Epoch 371/10001:  10%|█         | 1/10 [00:00<00:04,  1.84it/s, Loss=0.854]
+Epoch 371/10001:  60%|██████    | 6/10 [00:00<00:00, 11.80it/s, Loss=0.854]
+Epoch 371/10001:  60%|██████    | 6/10 [00:00<00:00, 11.80it/s, Loss=0.844]
+Epoch 371/10001:  60%|██████    | 6/10 [00:00<00:00, 11.80it/s, Loss=0.854]
+Epoch 371/10001:  60%|██████    | 6/10 [00:00<00:00, 11.80it/s, Loss=0.843]
+Epoch 371/10001:  60%|██████    | 6/10 [00:00<00:00, 11.80it/s, Loss=0.848]
+Epoch 371/10001: 100%|██████████| 10/10 [00:00<00:00, 11.83it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 372/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 372/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 372/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.855]
+Epoch 372/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.851]
+Epoch 372/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.842]
+Epoch 372/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.852]
+Epoch 372/10001:  40%|████      | 4/10 [00:00<00:00,  9.33it/s, Loss=0.852]
+Epoch 372/10001:  40%|████      | 4/10 [00:00<00:00,  9.33it/s, Loss=0.851]
+Epoch 372/10001:  40%|████      | 4/10 [00:00<00:00,  9.33it/s, Loss=0.853]
+Epoch 372/10001:  40%|████      | 4/10 [00:00<00:00,  9.33it/s, Loss=0.853]
+Epoch 372/10001:  40%|████      | 4/10 [00:00<00:00,  9.33it/s, Loss=0.854]
+Epoch 372/10001:  80%|████████  | 8/10 [00:00<00:00, 16.93it/s, Loss=0.854]
+Epoch 372/10001:  80%|████████  | 8/10 [00:00<00:00, 16.93it/s, Loss=0.854]
+Epoch 372/10001:  80%|████████  | 8/10 [00:00<00:00, 16.93it/s, Loss=0.853]
+Epoch 372/10001: 100%|██████████| 10/10 [00:00<00:00, 12.60it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 373/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 373/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 373/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.855]
+Epoch 373/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.843]
+Epoch 373/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.848]
+Epoch 373/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.85] 
+Epoch 373/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.85]
+Epoch 373/10001:  10%|█         | 1/10 [00:00<00:03,  2.94it/s, Loss=0.848]
+Epoch 373/10001:  60%|██████    | 6/10 [00:00<00:00, 16.68it/s, Loss=0.848]
+Epoch 373/10001:  60%|██████    | 6/10 [00:00<00:00, 16.68it/s, Loss=0.858]
+Epoch 373/10001:  60%|██████    | 6/10 [00:00<00:00, 16.68it/s, Loss=0.85] 
+Epoch 373/10001:  60%|██████    | 6/10 [00:00<00:00, 16.68it/s, Loss=0.845]
+Epoch 373/10001:  60%|██████    | 6/10 [00:00<00:00, 16.68it/s, Loss=0.855]
+Epoch 373/10001: 100%|██████████| 10/10 [00:00<00:00, 15.99it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 374/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 374/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 374/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.85]
+Epoch 374/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.853]
+Epoch 374/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.848]
+Epoch 374/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.853]
+Epoch 374/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.849]
+Epoch 374/10001:  10%|█         | 1/10 [00:00<00:04,  1.87it/s, Loss=0.856]
+Epoch 374/10001:  60%|██████    | 6/10 [00:00<00:00, 11.82it/s, Loss=0.856]
+Epoch 374/10001:  60%|██████    | 6/10 [00:00<00:00, 11.82it/s, Loss=0.842]
+Epoch 374/10001:  60%|██████    | 6/10 [00:00<00:00, 11.82it/s, Loss=0.847]
+Epoch 374/10001:  60%|██████    | 6/10 [00:00<00:00, 11.82it/s, Loss=0.858]
+Epoch 374/10001:  60%|██████    | 6/10 [00:00<00:00, 11.82it/s, Loss=0.858]
+Epoch 374/10001: 100%|██████████| 10/10 [00:00<00:00, 12.02it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 375/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 375/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 375/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.843]
+Epoch 375/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.847]
+Epoch 375/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.856]
+Epoch 375/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.86] 
+Epoch 375/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.851]
+Epoch 375/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.843]
+Epoch 375/10001:  60%|██████    | 6/10 [00:00<00:00, 16.05it/s, Loss=0.843]
+Epoch 375/10001:  60%|██████    | 6/10 [00:00<00:00, 16.05it/s, Loss=0.848]
+Epoch 375/10001:  60%|██████    | 6/10 [00:00<00:00, 16.05it/s, Loss=0.851]
+Epoch 375/10001:  60%|██████    | 6/10 [00:00<00:00, 16.05it/s, Loss=0.854]
+Epoch 375/10001:  60%|██████    | 6/10 [00:00<00:00, 16.05it/s, Loss=0.857]
+Epoch 375/10001: 100%|██████████| 10/10 [00:00<00:00, 15.90it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 376/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 376/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 376/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.849]
+Epoch 376/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.852]
+Epoch 376/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.854]
+Epoch 376/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.856]
+Epoch 376/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.854]
+Epoch 376/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.846]
+Epoch 376/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.847]
+Epoch 376/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.848]
+Epoch 376/10001:  80%|████████  | 8/10 [00:00<00:00, 22.10it/s, Loss=0.848]
+Epoch 376/10001:  80%|████████  | 8/10 [00:00<00:00, 22.10it/s, Loss=0.845]
+Epoch 376/10001:  80%|████████  | 8/10 [00:00<00:00, 22.10it/s, Loss=0.854]
+Epoch 376/10001: 100%|██████████| 10/10 [00:00<00:00, 16.77it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 377/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 377/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 377/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.845]
+Epoch 377/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.852]
+Epoch 377/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.849]
+Epoch 377/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.849]
+Epoch 377/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.859]
+Epoch 377/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.859]
+Epoch 377/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.85] 
+Epoch 377/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.847]
+Epoch 377/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.855]
+Epoch 377/10001:  50%|█████     | 5/10 [00:00<00:00, 12.44it/s, Loss=0.851]
+Epoch 377/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.29it/s, Loss=0.851]
+Epoch 377/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.29it/s, Loss=0.856]
+Epoch 377/10001: 100%|██████████| 10/10 [00:00<00:00, 13.56it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 378/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 378/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 378/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.858]
+Epoch 378/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.856]
+Epoch 378/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.853]
+Epoch 378/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.847]
+Epoch 378/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.859]
+Epoch 378/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.848]
+Epoch 378/10001:  60%|██████    | 6/10 [00:00<00:00, 13.57it/s, Loss=0.848]
+Epoch 378/10001:  60%|██████    | 6/10 [00:00<00:00, 13.57it/s, Loss=0.853]
+Epoch 378/10001:  60%|██████    | 6/10 [00:00<00:00, 13.57it/s, Loss=0.856]
+Epoch 378/10001:  60%|██████    | 6/10 [00:00<00:00, 13.57it/s, Loss=0.853]
+Epoch 378/10001:  60%|██████    | 6/10 [00:00<00:00, 13.57it/s, Loss=0.843]
+Epoch 378/10001: 100%|██████████| 10/10 [00:00<00:00, 13.42it/s, Loss=0.843]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 379/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 379/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 379/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.854]
+Epoch 379/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.852]
+Epoch 379/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.854]
+Epoch 379/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.854]
+Epoch 379/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.847]
+Epoch 379/10001:  50%|█████     | 5/10 [00:00<00:00, 11.00it/s, Loss=0.847]
+Epoch 379/10001:  50%|█████     | 5/10 [00:00<00:00, 11.00it/s, Loss=0.841]
+Epoch 379/10001:  50%|█████     | 5/10 [00:00<00:00, 11.00it/s, Loss=0.848]
+Epoch 379/10001:  50%|█████     | 5/10 [00:00<00:00, 11.00it/s, Loss=0.858]
+Epoch 379/10001:  50%|█████     | 5/10 [00:00<00:00, 11.00it/s, Loss=0.856]
+Epoch 379/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.66it/s, Loss=0.856]
+Epoch 379/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.66it/s, Loss=0.845]
+Epoch 379/10001: 100%|██████████| 10/10 [00:00<00:00, 12.39it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 380/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 380/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 380/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.848]
+Epoch 380/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.85] 
+Epoch 380/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.851]
+Epoch 380/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.846]
+Epoch 380/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.867]
+Epoch 380/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.852]
+Epoch 380/10001:  60%|██████    | 6/10 [00:00<00:00, 16.72it/s, Loss=0.852]
+Epoch 380/10001:  60%|██████    | 6/10 [00:00<00:00, 16.72it/s, Loss=0.846]
+Epoch 380/10001:  60%|██████    | 6/10 [00:00<00:00, 16.72it/s, Loss=0.852]
+Epoch 380/10001:  60%|██████    | 6/10 [00:00<00:00, 16.72it/s, Loss=0.85] 
+Epoch 380/10001:  60%|██████    | 6/10 [00:00<00:00, 16.72it/s, Loss=0.858]
+Epoch 380/10001: 100%|██████████| 10/10 [00:00<00:00, 15.89it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 381/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 381/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.861]
+Epoch 381/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.861]
+Epoch 381/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.852]
+Epoch 381/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.854]
+Epoch 381/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.845]
+Epoch 381/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.855]
+Epoch 381/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.851]
+Epoch 381/10001:  60%|██████    | 6/10 [00:00<00:00, 13.64it/s, Loss=0.851]
+Epoch 381/10001:  60%|██████    | 6/10 [00:00<00:00, 13.64it/s, Loss=0.857]
+Epoch 381/10001:  60%|██████    | 6/10 [00:00<00:00, 13.64it/s, Loss=0.847]
+Epoch 381/10001:  60%|██████    | 6/10 [00:00<00:00, 13.64it/s, Loss=0.852]
+Epoch 381/10001:  60%|██████    | 6/10 [00:00<00:00, 13.64it/s, Loss=0.859]
+Epoch 381/10001: 100%|██████████| 10/10 [00:00<00:00, 20.08it/s, Loss=0.859]
+Epoch 381/10001: 100%|██████████| 10/10 [00:00<00:00, 13.12it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 382/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 382/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 382/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.845]
+Epoch 382/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.853]
+Epoch 382/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.845]
+Epoch 382/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.845]
+Epoch 382/10001:  40%|████      | 4/10 [00:00<00:00, 10.57it/s, Loss=0.845]
+Epoch 382/10001:  40%|████      | 4/10 [00:00<00:00, 10.57it/s, Loss=0.845]
+Epoch 382/10001:  40%|████      | 4/10 [00:00<00:00, 10.57it/s, Loss=0.847]
+Epoch 382/10001:  40%|████      | 4/10 [00:00<00:00, 10.57it/s, Loss=0.851]
+Epoch 382/10001:  40%|████      | 4/10 [00:00<00:00, 10.57it/s, Loss=0.849]
+Epoch 382/10001:  80%|████████  | 8/10 [00:00<00:00, 18.88it/s, Loss=0.849]
+Epoch 382/10001:  80%|████████  | 8/10 [00:00<00:00, 18.88it/s, Loss=0.853]
+Epoch 382/10001:  80%|████████  | 8/10 [00:00<00:00, 18.88it/s, Loss=0.853]
+Epoch 382/10001: 100%|██████████| 10/10 [00:00<00:00, 13.19it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 383/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 383/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 383/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.843]
+Epoch 383/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.858]
+Epoch 383/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.842]
+Epoch 383/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.861]
+Epoch 383/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.848]
+Epoch 383/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.856]
+Epoch 383/10001:  60%|██████    | 6/10 [00:00<00:00, 16.59it/s, Loss=0.856]
+Epoch 383/10001:  60%|██████    | 6/10 [00:00<00:00, 16.59it/s, Loss=0.852]
+Epoch 383/10001:  60%|██████    | 6/10 [00:00<00:00, 16.59it/s, Loss=0.85] 
+Epoch 383/10001:  60%|██████    | 6/10 [00:00<00:00, 16.59it/s, Loss=0.845]
+Epoch 383/10001:  60%|██████    | 6/10 [00:00<00:00, 16.59it/s, Loss=0.845]
+Epoch 383/10001: 100%|██████████| 10/10 [00:00<00:00, 15.93it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 384/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 384/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 384/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.854]
+Epoch 384/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.843]
+Epoch 384/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.851]
+Epoch 384/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.853]
+Epoch 384/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.853]
+Epoch 384/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.851]
+Epoch 384/10001:  60%|██████    | 6/10 [00:00<00:00, 15.38it/s, Loss=0.851]
+Epoch 384/10001:  60%|██████    | 6/10 [00:00<00:00, 15.38it/s, Loss=0.843]
+Epoch 384/10001:  60%|██████    | 6/10 [00:00<00:00, 15.38it/s, Loss=0.851]
+Epoch 384/10001:  60%|██████    | 6/10 [00:00<00:00, 15.38it/s, Loss=0.856]
+Epoch 384/10001:  60%|██████    | 6/10 [00:00<00:00, 15.38it/s, Loss=0.848]
+Epoch 384/10001: 100%|██████████| 10/10 [00:00<00:00, 15.51it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 385/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 385/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 385/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.854]
+Epoch 385/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.856]
+Epoch 385/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.849]
+Epoch 385/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.845]
+Epoch 385/10001:  10%|█         | 1/10 [00:00<00:03,  2.71it/s, Loss=0.855]
+Epoch 385/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.855]
+Epoch 385/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.849]
+Epoch 385/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.856]
+Epoch 385/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.855]
+Epoch 385/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.852]
+Epoch 385/10001:  50%|█████     | 5/10 [00:00<00:00, 12.61it/s, Loss=0.846]
+Epoch 385/10001: 100%|██████████| 10/10 [00:00<00:00, 22.73it/s, Loss=0.846]
+Epoch 385/10001: 100%|██████████| 10/10 [00:00<00:00, 14.57it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 386/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 386/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 386/10001:  10%|█         | 1/10 [00:00<00:04,  1.95it/s, Loss=0.853]
+Epoch 386/10001:  10%|█         | 1/10 [00:00<00:04,  1.95it/s, Loss=0.847]
+Epoch 386/10001:  10%|█         | 1/10 [00:00<00:04,  1.95it/s, Loss=0.85] 
+Epoch 386/10001:  10%|█         | 1/10 [00:00<00:04,  1.95it/s, Loss=0.848]
+Epoch 386/10001:  10%|█         | 1/10 [00:00<00:04,  1.95it/s, Loss=0.852]
+Epoch 386/10001:  10%|█         | 1/10 [00:00<00:04,  1.95it/s, Loss=0.853]
+Epoch 386/10001:  60%|██████    | 6/10 [00:00<00:00, 12.16it/s, Loss=0.853]
+Epoch 386/10001:  60%|██████    | 6/10 [00:00<00:00, 12.16it/s, Loss=0.858]
+Epoch 386/10001:  60%|██████    | 6/10 [00:00<00:00, 12.16it/s, Loss=0.859]
+Epoch 386/10001:  60%|██████    | 6/10 [00:00<00:00, 12.16it/s, Loss=0.859]
+Epoch 386/10001:  60%|██████    | 6/10 [00:00<00:00, 12.16it/s, Loss=0.859]
+Epoch 386/10001: 100%|██████████| 10/10 [00:00<00:00, 12.66it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 387/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 387/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 387/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.847]
+Epoch 387/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.849]
+Epoch 387/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.852]
+Epoch 387/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.855]
+Epoch 387/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.854]
+Epoch 387/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.845]
+Epoch 387/10001:  60%|██████    | 6/10 [00:00<00:00, 13.95it/s, Loss=0.845]
+Epoch 387/10001:  60%|██████    | 6/10 [00:00<00:00, 13.95it/s, Loss=0.85] 
+Epoch 387/10001:  60%|██████    | 6/10 [00:00<00:00, 13.95it/s, Loss=0.85]
+Epoch 387/10001:  60%|██████    | 6/10 [00:00<00:00, 13.95it/s, Loss=0.857]
+Epoch 387/10001:  60%|██████    | 6/10 [00:00<00:00, 13.95it/s, Loss=0.851]
+Epoch 387/10001: 100%|██████████| 10/10 [00:00<00:00, 13.73it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 388/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 388/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.84]
+Epoch 388/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.84]
+Epoch 388/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.861]
+Epoch 388/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.851]
+Epoch 388/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.851]
+Epoch 388/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.852]
+Epoch 388/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.843]
+Epoch 388/10001:  60%|██████    | 6/10 [00:00<00:00, 12.87it/s, Loss=0.843]
+Epoch 388/10001:  60%|██████    | 6/10 [00:00<00:00, 12.87it/s, Loss=0.847]
+Epoch 388/10001:  60%|██████    | 6/10 [00:00<00:00, 12.87it/s, Loss=0.854]
+Epoch 388/10001:  60%|██████    | 6/10 [00:00<00:00, 12.87it/s, Loss=0.858]
+Epoch 388/10001:  60%|██████    | 6/10 [00:00<00:00, 12.87it/s, Loss=0.855]
+Epoch 388/10001: 100%|██████████| 10/10 [00:00<00:00, 13.05it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 389/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 389/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 389/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.856]
+Epoch 389/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.848]
+Epoch 389/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.845]
+Epoch 389/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.849]
+Epoch 389/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.86] 
+Epoch 389/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.844]
+Epoch 389/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.844]
+Epoch 389/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.851]
+Epoch 389/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.849]
+Epoch 389/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.851]
+Epoch 389/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.853]
+Epoch 389/10001: 100%|██████████| 10/10 [00:00<00:00, 13.82it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 390/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 390/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 390/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.851]
+Epoch 390/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.849]
+Epoch 390/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.853]
+Epoch 390/10001:  10%|█         | 1/10 [00:00<00:03,  2.85it/s, Loss=0.847]
+Epoch 390/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.847]
+Epoch 390/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.844]
+Epoch 390/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.854]
+Epoch 390/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.855]
+Epoch 390/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.857]
+Epoch 390/10001:  40%|████      | 4/10 [00:00<00:00, 10.65it/s, Loss=0.86] 
+Epoch 390/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.63it/s, Loss=0.86]
+Epoch 390/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.63it/s, Loss=0.851]
+Epoch 390/10001: 100%|██████████| 10/10 [00:00<00:00, 14.01it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 391/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 391/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 391/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.849]
+Epoch 391/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.851]
+Epoch 391/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.847]
+Epoch 391/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.849]
+Epoch 391/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.847]
+Epoch 391/10001:  10%|█         | 1/10 [00:00<00:03,  2.99it/s, Loss=0.848]
+Epoch 391/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.848]
+Epoch 391/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.85] 
+Epoch 391/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.854]
+Epoch 391/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.854]
+Epoch 391/10001:  60%|██████    | 6/10 [00:00<00:00, 16.65it/s, Loss=0.846]
+Epoch 391/10001: 100%|██████████| 10/10 [00:00<00:00, 15.57it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 392/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 392/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.859]
+Epoch 392/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.859]
+Epoch 392/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.856]
+Epoch 392/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.855]
+Epoch 392/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.846]
+Epoch 392/10001:  40%|████      | 4/10 [00:00<00:00,  9.34it/s, Loss=0.846]
+Epoch 392/10001:  40%|████      | 4/10 [00:00<00:00,  9.34it/s, Loss=0.851]
+Epoch 392/10001:  40%|████      | 4/10 [00:00<00:00,  9.34it/s, Loss=0.855]
+Epoch 392/10001:  40%|████      | 4/10 [00:00<00:00,  9.34it/s, Loss=0.848]
+Epoch 392/10001:  40%|████      | 4/10 [00:00<00:00,  9.34it/s, Loss=0.858]
+Epoch 392/10001:  80%|████████  | 8/10 [00:00<00:00, 16.95it/s, Loss=0.858]
+Epoch 392/10001:  80%|████████  | 8/10 [00:00<00:00, 16.95it/s, Loss=0.854]
+Epoch 392/10001:  80%|████████  | 8/10 [00:00<00:00, 16.95it/s, Loss=0.85] 
+Epoch 392/10001: 100%|██████████| 10/10 [00:00<00:00, 12.02it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 393/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 393/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 393/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.855]
+Epoch 393/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.848]
+Epoch 393/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.852]
+Epoch 393/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.861]
+Epoch 393/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.864]
+Epoch 393/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.846]
+Epoch 393/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.846]
+Epoch 393/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.854]
+Epoch 393/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.85] 
+Epoch 393/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.858]
+Epoch 393/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.851]
+Epoch 393/10001: 100%|██████████| 10/10 [00:00<00:00, 19.47it/s, Loss=0.851]
+Epoch 393/10001: 100%|██████████| 10/10 [00:00<00:00, 12.76it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 394/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 394/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 394/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.852]
+Epoch 394/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.859]
+Epoch 394/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.846]
+Epoch 394/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.846]
+Epoch 394/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.857]
+Epoch 394/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.857]
+Epoch 394/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.857]
+Epoch 394/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.851]
+Epoch 394/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.847]
+Epoch 394/10001:  50%|█████     | 5/10 [00:00<00:00, 11.19it/s, Loss=0.852]
+Epoch 394/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.28it/s, Loss=0.852]
+Epoch 394/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.28it/s, Loss=0.841]
+Epoch 394/10001: 100%|██████████| 10/10 [00:00<00:00, 12.46it/s, Loss=0.841]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 395/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 395/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 395/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.85]
+Epoch 395/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.847]
+Epoch 395/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.847]
+Epoch 395/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.854]
+Epoch 395/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.856]
+Epoch 395/10001:  50%|█████     | 5/10 [00:00<00:00, 11.06it/s, Loss=0.856]
+Epoch 395/10001:  50%|█████     | 5/10 [00:00<00:00, 11.06it/s, Loss=0.854]
+Epoch 395/10001:  50%|█████     | 5/10 [00:00<00:00, 11.06it/s, Loss=0.853]
+Epoch 395/10001:  50%|█████     | 5/10 [00:00<00:00, 11.06it/s, Loss=0.851]
+Epoch 395/10001:  50%|█████     | 5/10 [00:00<00:00, 11.06it/s, Loss=0.841]
+Epoch 395/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.88it/s, Loss=0.841]
+Epoch 395/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.88it/s, Loss=0.85] 
+Epoch 395/10001: 100%|██████████| 10/10 [00:00<00:00, 12.43it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 396/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 396/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 396/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.852]
+Epoch 396/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.855]
+Epoch 396/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.848]
+Epoch 396/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 396/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.85] 
+Epoch 396/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.85]
+Epoch 396/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.853]
+Epoch 396/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.855]
+Epoch 396/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.85] 
+Epoch 396/10001:  50%|█████     | 5/10 [00:00<00:00, 11.58it/s, Loss=0.851]
+Epoch 396/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.43it/s, Loss=0.851]
+Epoch 396/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.43it/s, Loss=0.85] 
+Epoch 396/10001: 100%|██████████| 10/10 [00:00<00:00, 12.71it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 397/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 397/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 397/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.851]
+Epoch 397/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.842]
+Epoch 397/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.846]
+Epoch 397/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.851]
+Epoch 397/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.857]
+Epoch 397/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.854]
+Epoch 397/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.854]
+Epoch 397/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.859]
+Epoch 397/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.857]
+Epoch 397/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.864]
+Epoch 397/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.85] 
+Epoch 397/10001: 100%|██████████| 10/10 [00:00<00:00, 22.00it/s, Loss=0.85]
+Epoch 397/10001: 100%|██████████| 10/10 [00:00<00:00, 14.73it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 398/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 398/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 398/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.852]
+Epoch 398/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.851]
+Epoch 398/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.854]
+Epoch 398/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.858]
+Epoch 398/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.848]
+Epoch 398/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.848]
+Epoch 398/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.852]
+Epoch 398/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.849]
+Epoch 398/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.851]
+Epoch 398/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.838]
+Epoch 398/10001:  50%|█████     | 5/10 [00:00<00:00, 12.28it/s, Loss=0.851]
+Epoch 398/10001: 100%|██████████| 10/10 [00:00<00:00, 14.04it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 399/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 399/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 399/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.854]
+Epoch 399/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.851]
+Epoch 399/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.85] 
+Epoch 399/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.852]
+Epoch 399/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.846]
+Epoch 399/10001:  10%|█         | 1/10 [00:00<00:03,  2.89it/s, Loss=0.855]
+Epoch 399/10001:  60%|██████    | 6/10 [00:00<00:00, 16.08it/s, Loss=0.855]
+Epoch 399/10001:  60%|██████    | 6/10 [00:00<00:00, 16.08it/s, Loss=0.843]
+Epoch 399/10001:  60%|██████    | 6/10 [00:00<00:00, 16.08it/s, Loss=0.85] 
+Epoch 399/10001:  60%|██████    | 6/10 [00:00<00:00, 16.08it/s, Loss=0.85]
+Epoch 399/10001:  60%|██████    | 6/10 [00:00<00:00, 16.08it/s, Loss=0.845]
+Epoch 399/10001: 100%|██████████| 10/10 [00:00<00:00, 15.25it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 400/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 400/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 400/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.849]
+Epoch 400/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.852]
+Epoch 400/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.851]
+Epoch 400/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.848]
+Epoch 400/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.851]
+Epoch 400/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.851]
+Epoch 400/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.845]
+Epoch 400/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.857]
+Epoch 400/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.845]
+Epoch 400/10001:  50%|█████     | 5/10 [00:00<00:00, 11.28it/s, Loss=0.852]
+Epoch 400/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.43it/s, Loss=0.852]
+Epoch 400/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.43it/s, Loss=0.851]
+Epoch 400/10001: 100%|██████████| 10/10 [00:00<00:00, 12.85it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 401/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 401/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 401/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.851]
+Epoch 401/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.856]
+Epoch 401/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.85] 
+Epoch 401/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.845]
+Epoch 401/10001:  40%|████      | 4/10 [00:00<00:00, 10.82it/s, Loss=0.845]
+Epoch 401/10001:  40%|████      | 4/10 [00:00<00:00, 10.82it/s, Loss=0.858]
+Epoch 401/10001:  40%|████      | 4/10 [00:00<00:00, 10.82it/s, Loss=0.847]
+Epoch 401/10001:  40%|████      | 4/10 [00:00<00:00, 10.82it/s, Loss=0.855]
+Epoch 401/10001:  40%|████      | 4/10 [00:00<00:00, 10.82it/s, Loss=0.852]
+Epoch 401/10001:  80%|████████  | 8/10 [00:00<00:00, 18.43it/s, Loss=0.852]
+Epoch 401/10001:  80%|████████  | 8/10 [00:00<00:00, 18.43it/s, Loss=0.849]
+Epoch 401/10001:  80%|████████  | 8/10 [00:00<00:00, 18.43it/s, Loss=0.849]
+Epoch 401/10001: 100%|██████████| 10/10 [00:00<00:00, 13.76it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 402/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 402/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 402/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.851]
+Epoch 402/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.849]
+Epoch 402/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.855]
+Epoch 402/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.846]
+Epoch 402/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.848]
+Epoch 402/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.849]
+Epoch 402/10001:  60%|██████    | 6/10 [00:00<00:00, 16.02it/s, Loss=0.849]
+Epoch 402/10001:  60%|██████    | 6/10 [00:00<00:00, 16.02it/s, Loss=0.854]
+Epoch 402/10001:  60%|██████    | 6/10 [00:00<00:00, 16.02it/s, Loss=0.854]
+Epoch 402/10001:  60%|██████    | 6/10 [00:00<00:00, 16.02it/s, Loss=0.855]
+Epoch 402/10001:  60%|██████    | 6/10 [00:00<00:00, 16.02it/s, Loss=0.847]
+Epoch 402/10001: 100%|██████████| 10/10 [00:00<00:00, 15.26it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 403/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 403/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 403/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.854]
+Epoch 403/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.85] 
+Epoch 403/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.857]
+Epoch 403/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.847]
+Epoch 403/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.849]
+Epoch 403/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.849]
+Epoch 403/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.853]
+Epoch 403/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.85] 
+Epoch 403/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.852]
+Epoch 403/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.855]
+Epoch 403/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.53it/s, Loss=0.855]
+Epoch 403/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.53it/s, Loss=0.849]
+Epoch 403/10001: 100%|██████████| 10/10 [00:00<00:00, 13.17it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 404/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 404/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 404/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.856]
+Epoch 404/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.858]
+Epoch 404/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.852]
+Epoch 404/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.854]
+Epoch 404/10001:  40%|████      | 4/10 [00:00<00:00, 11.00it/s, Loss=0.854]
+Epoch 404/10001:  40%|████      | 4/10 [00:00<00:00, 11.00it/s, Loss=0.849]
+Epoch 404/10001:  40%|████      | 4/10 [00:00<00:00, 11.00it/s, Loss=0.857]
+Epoch 404/10001:  40%|████      | 4/10 [00:00<00:00, 11.00it/s, Loss=0.849]
+Epoch 404/10001:  40%|████      | 4/10 [00:00<00:00, 11.00it/s, Loss=0.85] 
+Epoch 404/10001:  40%|████      | 4/10 [00:00<00:00, 11.00it/s, Loss=0.861]
+Epoch 404/10001:  90%|█████████ | 9/10 [00:00<00:00, 22.51it/s, Loss=0.861]
+Epoch 404/10001:  90%|█████████ | 9/10 [00:00<00:00, 22.51it/s, Loss=0.848]
+Epoch 404/10001: 100%|██████████| 10/10 [00:00<00:00, 14.52it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 405/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 405/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 405/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.853]
+Epoch 405/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.844]
+Epoch 405/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.862]
+Epoch 405/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.846]
+Epoch 405/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.854]
+Epoch 405/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.854]
+Epoch 405/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.85] 
+Epoch 405/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.858]
+Epoch 405/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.854]
+Epoch 405/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.843]
+Epoch 405/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.854]
+Epoch 405/10001: 100%|██████████| 10/10 [00:00<00:00, 20.28it/s, Loss=0.854]
+Epoch 405/10001: 100%|██████████| 10/10 [00:00<00:00, 12.40it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 406/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 406/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 406/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.852]
+Epoch 406/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.853]
+Epoch 406/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.848]
+Epoch 406/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.852]
+Epoch 406/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.852]
+Epoch 406/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.855]
+Epoch 406/10001:  60%|██████    | 6/10 [00:00<00:00, 15.05it/s, Loss=0.855]
+Epoch 406/10001:  60%|██████    | 6/10 [00:00<00:00, 15.05it/s, Loss=0.858]
+Epoch 406/10001:  60%|██████    | 6/10 [00:00<00:00, 15.05it/s, Loss=0.856]
+Epoch 406/10001:  60%|██████    | 6/10 [00:00<00:00, 15.05it/s, Loss=0.853]
+Epoch 406/10001:  60%|██████    | 6/10 [00:00<00:00, 15.05it/s, Loss=0.851]
+Epoch 406/10001: 100%|██████████| 10/10 [00:00<00:00, 13.79it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 407/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 407/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 407/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.852]
+Epoch 407/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.847]
+Epoch 407/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.853]
+Epoch 407/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.851]
+Epoch 407/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.846]
+Epoch 407/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.853]
+Epoch 407/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.853]
+Epoch 407/10001:  70%|███████   | 7/10 [00:00<00:00, 16.92it/s, Loss=0.853]
+Epoch 407/10001:  70%|███████   | 7/10 [00:00<00:00, 16.92it/s, Loss=0.845]
+Epoch 407/10001:  70%|███████   | 7/10 [00:00<00:00, 16.92it/s, Loss=0.853]
+Epoch 407/10001:  70%|███████   | 7/10 [00:00<00:00, 16.92it/s, Loss=0.848]
+Epoch 407/10001: 100%|██████████| 10/10 [00:00<00:00, 14.53it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 408/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 408/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 408/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.857]
+Epoch 408/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.846]
+Epoch 408/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.85] 
+Epoch 408/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.852]
+Epoch 408/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.852]
+Epoch 408/10001:  50%|█████     | 5/10 [00:00<00:00, 12.15it/s, Loss=0.852]
+Epoch 408/10001:  50%|█████     | 5/10 [00:00<00:00, 12.15it/s, Loss=0.853]
+Epoch 408/10001:  50%|█████     | 5/10 [00:00<00:00, 12.15it/s, Loss=0.845]
+Epoch 408/10001:  50%|█████     | 5/10 [00:00<00:00, 12.15it/s, Loss=0.854]
+Epoch 408/10001:  50%|█████     | 5/10 [00:00<00:00, 12.15it/s, Loss=0.852]
+Epoch 408/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.88it/s, Loss=0.852]
+Epoch 408/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.88it/s, Loss=0.854]
+Epoch 408/10001: 100%|██████████| 10/10 [00:00<00:00, 13.24it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 409/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 409/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 409/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.858]
+Epoch 409/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.845]
+Epoch 409/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.854]
+Epoch 409/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.85] 
+Epoch 409/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.844]
+Epoch 409/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.852]
+Epoch 409/10001:  60%|██████    | 6/10 [00:00<00:00, 16.61it/s, Loss=0.852]
+Epoch 409/10001:  60%|██████    | 6/10 [00:00<00:00, 16.61it/s, Loss=0.849]
+Epoch 409/10001:  60%|██████    | 6/10 [00:00<00:00, 16.61it/s, Loss=0.849]
+Epoch 409/10001:  60%|██████    | 6/10 [00:00<00:00, 16.61it/s, Loss=0.86] 
+Epoch 409/10001:  60%|██████    | 6/10 [00:00<00:00, 16.61it/s, Loss=0.849]
+Epoch 409/10001: 100%|██████████| 10/10 [00:00<00:00, 15.86it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 410/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 410/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 410/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.85]
+Epoch 410/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.849]
+Epoch 410/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.849]
+Epoch 410/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.853]
+Epoch 410/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.848]
+Epoch 410/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.848]
+Epoch 410/10001:  60%|██████    | 6/10 [00:00<00:00, 16.26it/s, Loss=0.848]
+Epoch 410/10001:  60%|██████    | 6/10 [00:00<00:00, 16.26it/s, Loss=0.847]
+Epoch 410/10001:  60%|██████    | 6/10 [00:00<00:00, 16.26it/s, Loss=0.847]
+Epoch 410/10001:  60%|██████    | 6/10 [00:00<00:00, 16.26it/s, Loss=0.853]
+Epoch 410/10001:  60%|██████    | 6/10 [00:00<00:00, 16.26it/s, Loss=0.852]
+Epoch 410/10001: 100%|██████████| 10/10 [00:00<00:00, 16.04it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 411/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 411/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 411/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.857]
+Epoch 411/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.853]
+Epoch 411/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.846]
+Epoch 411/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.849]
+Epoch 411/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.854]
+Epoch 411/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.854]
+Epoch 411/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.854]
+Epoch 411/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.849]
+Epoch 411/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.844]
+Epoch 411/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.85] 
+Epoch 411/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.854]
+Epoch 411/10001: 100%|██████████| 10/10 [00:00<00:00, 13.71it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 412/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 412/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 412/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.85]
+Epoch 412/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.852]
+Epoch 412/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.848]
+Epoch 412/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.848]
+Epoch 412/10001:  40%|████      | 4/10 [00:00<00:00, 10.43it/s, Loss=0.848]
+Epoch 412/10001:  40%|████      | 4/10 [00:00<00:00, 10.43it/s, Loss=0.856]
+Epoch 412/10001:  40%|████      | 4/10 [00:00<00:00, 10.43it/s, Loss=0.853]
+Epoch 412/10001:  40%|████      | 4/10 [00:00<00:00, 10.43it/s, Loss=0.853]
+Epoch 412/10001:  40%|████      | 4/10 [00:00<00:00, 10.43it/s, Loss=0.845]
+Epoch 412/10001:  40%|████      | 4/10 [00:00<00:00, 10.43it/s, Loss=0.852]
+Epoch 412/10001:  40%|████      | 4/10 [00:00<00:00, 10.43it/s, Loss=0.859]
+Epoch 412/10001: 100%|██████████| 10/10 [00:00<00:00, 23.78it/s, Loss=0.859]
+Epoch 412/10001: 100%|██████████| 10/10 [00:00<00:00, 14.57it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 413/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 413/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 413/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.846]
+Epoch 413/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.85] 
+Epoch 413/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.848]
+Epoch 413/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.849]
+Epoch 413/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.855]
+Epoch 413/10001:  10%|█         | 1/10 [00:00<00:02,  3.00it/s, Loss=0.85] 
+Epoch 413/10001:  60%|██████    | 6/10 [00:00<00:00, 17.05it/s, Loss=0.85]
+Epoch 413/10001:  60%|██████    | 6/10 [00:00<00:00, 17.05it/s, Loss=0.843]
+Epoch 413/10001:  60%|██████    | 6/10 [00:00<00:00, 17.05it/s, Loss=0.846]
+Epoch 413/10001:  60%|██████    | 6/10 [00:00<00:00, 17.05it/s, Loss=0.859]
+Epoch 413/10001:  60%|██████    | 6/10 [00:00<00:00, 17.05it/s, Loss=0.854]
+Epoch 413/10001: 100%|██████████| 10/10 [00:00<00:00, 16.12it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 414/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 414/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.841]
+Epoch 414/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.841]
+Epoch 414/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.851]
+Epoch 414/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.839]
+Epoch 414/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.849]
+Epoch 414/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.862]
+Epoch 414/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.847]
+Epoch 414/10001:  60%|██████    | 6/10 [00:00<00:00, 16.91it/s, Loss=0.847]
+Epoch 414/10001:  60%|██████    | 6/10 [00:00<00:00, 16.91it/s, Loss=0.85] 
+Epoch 414/10001:  60%|██████    | 6/10 [00:00<00:00, 16.91it/s, Loss=0.844]
+Epoch 414/10001:  60%|██████    | 6/10 [00:00<00:00, 16.91it/s, Loss=0.844]
+Epoch 414/10001:  60%|██████    | 6/10 [00:00<00:00, 16.91it/s, Loss=0.858]
+Epoch 414/10001: 100%|██████████| 10/10 [00:00<00:00, 16.03it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 415/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 415/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 415/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.853]
+Epoch 415/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.844]
+Epoch 415/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.853]
+Epoch 415/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.853]
+Epoch 415/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.85] 
+Epoch 415/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.85]
+Epoch 415/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.85]
+Epoch 415/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.858]
+Epoch 415/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.848]
+Epoch 415/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.849]
+Epoch 415/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.78it/s, Loss=0.849]
+Epoch 415/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.78it/s, Loss=0.854]
+Epoch 415/10001: 100%|██████████| 10/10 [00:00<00:00, 13.30it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 416/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 416/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 416/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.845]
+Epoch 416/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.85] 
+Epoch 416/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.851]
+Epoch 416/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.849]
+Epoch 416/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.852]
+Epoch 416/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.853]
+Epoch 416/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.852]
+Epoch 416/10001:  70%|███████   | 7/10 [00:00<00:00, 17.91it/s, Loss=0.852]
+Epoch 416/10001:  70%|███████   | 7/10 [00:00<00:00, 17.91it/s, Loss=0.847]
+Epoch 416/10001:  70%|███████   | 7/10 [00:00<00:00, 17.91it/s, Loss=0.848]
+Epoch 416/10001:  70%|███████   | 7/10 [00:00<00:00, 17.91it/s, Loss=0.844]
+Epoch 416/10001: 100%|██████████| 10/10 [00:00<00:00, 15.76it/s, Loss=0.844]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 417/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 417/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 417/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.845]
+Epoch 417/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.851]
+Epoch 417/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.857]
+Epoch 417/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.849]
+Epoch 417/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.851]
+Epoch 417/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.848]
+Epoch 417/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.848]
+Epoch 417/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.849]
+Epoch 417/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.85] 
+Epoch 417/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.85]
+Epoch 417/10001:  60%|██████    | 6/10 [00:00<00:00, 15.90it/s, Loss=0.849]
+Epoch 417/10001: 100%|██████████| 10/10 [00:00<00:00, 15.48it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 418/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 418/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 418/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.847]
+Epoch 418/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.851]
+Epoch 418/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.858]
+Epoch 418/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.85] 
+Epoch 418/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.846]
+Epoch 418/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.847]
+Epoch 418/10001:  60%|██████    | 6/10 [00:00<00:00, 15.06it/s, Loss=0.847]
+Epoch 418/10001:  60%|██████    | 6/10 [00:00<00:00, 15.06it/s, Loss=0.856]
+Epoch 418/10001:  60%|██████    | 6/10 [00:00<00:00, 15.06it/s, Loss=0.849]
+Epoch 418/10001:  60%|██████    | 6/10 [00:00<00:00, 15.06it/s, Loss=0.857]
+Epoch 418/10001:  60%|██████    | 6/10 [00:00<00:00, 15.06it/s, Loss=0.857]
+Epoch 418/10001: 100%|██████████| 10/10 [00:00<00:00, 21.25it/s, Loss=0.857]
+Epoch 418/10001: 100%|██████████| 10/10 [00:00<00:00, 13.33it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 419/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 419/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 419/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.856]
+Epoch 419/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.853]
+Epoch 419/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.852]
+Epoch 419/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.854]
+Epoch 419/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.859]
+Epoch 419/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.852]
+Epoch 419/10001:  60%|██████    | 6/10 [00:00<00:00, 14.89it/s, Loss=0.852]
+Epoch 419/10001:  60%|██████    | 6/10 [00:00<00:00, 14.89it/s, Loss=0.855]
+Epoch 419/10001:  60%|██████    | 6/10 [00:00<00:00, 14.89it/s, Loss=0.85] 
+Epoch 419/10001:  60%|██████    | 6/10 [00:00<00:00, 14.89it/s, Loss=0.844]
+Epoch 419/10001:  60%|██████    | 6/10 [00:00<00:00, 14.89it/s, Loss=0.846]
+Epoch 419/10001: 100%|██████████| 10/10 [00:00<00:00, 14.56it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 420/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 420/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 420/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.847]
+Epoch 420/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.858]
+Epoch 420/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.854]
+Epoch 420/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.848]
+Epoch 420/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.849]
+Epoch 420/10001:  50%|█████     | 5/10 [00:00<00:00, 11.77it/s, Loss=0.849]
+Epoch 420/10001:  50%|█████     | 5/10 [00:00<00:00, 11.77it/s, Loss=0.841]
+Epoch 420/10001:  50%|█████     | 5/10 [00:00<00:00, 11.77it/s, Loss=0.85] 
+Epoch 420/10001:  50%|█████     | 5/10 [00:00<00:00, 11.77it/s, Loss=0.842]
+Epoch 420/10001:  50%|█████     | 5/10 [00:00<00:00, 11.77it/s, Loss=0.849]
+Epoch 420/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.61it/s, Loss=0.849]
+Epoch 420/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.61it/s, Loss=0.857]
+Epoch 420/10001: 100%|██████████| 10/10 [00:00<00:00, 13.10it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 421/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 421/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 421/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.848]
+Epoch 421/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.848]
+Epoch 421/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.85] 
+Epoch 421/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.855]
+Epoch 421/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.855]
+Epoch 421/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.845]
+Epoch 421/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.843]
+Epoch 421/10001:  70%|███████   | 7/10 [00:00<00:00, 18.19it/s, Loss=0.843]
+Epoch 421/10001:  70%|███████   | 7/10 [00:00<00:00, 18.19it/s, Loss=0.854]
+Epoch 421/10001:  70%|███████   | 7/10 [00:00<00:00, 18.19it/s, Loss=0.846]
+Epoch 421/10001:  70%|███████   | 7/10 [00:00<00:00, 18.19it/s, Loss=0.854]
+Epoch 421/10001: 100%|██████████| 10/10 [00:00<00:00, 15.73it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 422/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 422/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 422/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.849]
+Epoch 422/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.853]
+Epoch 422/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.854]
+Epoch 422/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.848]
+Epoch 422/10001:  10%|█         | 1/10 [00:00<00:03,  2.59it/s, Loss=0.85] 
+Epoch 422/10001:  50%|█████     | 5/10 [00:00<00:00, 12.52it/s, Loss=0.85]
+Epoch 422/10001:  50%|█████     | 5/10 [00:00<00:00, 12.52it/s, Loss=0.857]
+Epoch 422/10001:  50%|█████     | 5/10 [00:00<00:00, 12.52it/s, Loss=0.848]
+Epoch 422/10001:  50%|█████     | 5/10 [00:00<00:00, 12.52it/s, Loss=0.852]
+Epoch 422/10001:  50%|█████     | 5/10 [00:00<00:00, 12.52it/s, Loss=0.851]
+Epoch 422/10001:  50%|█████     | 5/10 [00:00<00:00, 12.52it/s, Loss=0.842]
+Epoch 422/10001: 100%|██████████| 10/10 [00:00<00:00, 22.62it/s, Loss=0.842]
+Epoch 422/10001: 100%|██████████| 10/10 [00:00<00:00, 14.15it/s, Loss=0.842]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 423/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 423/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 423/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.843]
+Epoch 423/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.852]
+Epoch 423/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.851]
+Epoch 423/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.848]
+Epoch 423/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.852]
+Epoch 423/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.852]
+Epoch 423/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.851]
+Epoch 423/10001:  70%|███████   | 7/10 [00:00<00:00, 16.63it/s, Loss=0.851]
+Epoch 423/10001:  70%|███████   | 7/10 [00:00<00:00, 16.63it/s, Loss=0.846]
+Epoch 423/10001:  70%|███████   | 7/10 [00:00<00:00, 16.63it/s, Loss=0.859]
+Epoch 423/10001:  70%|███████   | 7/10 [00:00<00:00, 16.63it/s, Loss=0.852]
+Epoch 423/10001: 100%|██████████| 10/10 [00:00<00:00, 14.36it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 424/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 424/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 424/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.854]
+Epoch 424/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.85] 
+Epoch 424/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.851]
+Epoch 424/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.847]
+Epoch 424/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.851]
+Epoch 424/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.85] 
+Epoch 424/10001:  60%|██████    | 6/10 [00:00<00:00, 15.53it/s, Loss=0.85]
+Epoch 424/10001:  60%|██████    | 6/10 [00:00<00:00, 15.53it/s, Loss=0.853]
+Epoch 424/10001:  60%|██████    | 6/10 [00:00<00:00, 15.53it/s, Loss=0.852]
+Epoch 424/10001:  60%|██████    | 6/10 [00:00<00:00, 15.53it/s, Loss=0.851]
+Epoch 424/10001:  60%|██████    | 6/10 [00:00<00:00, 15.53it/s, Loss=0.849]
+Epoch 424/10001: 100%|██████████| 10/10 [00:00<00:00, 14.80it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 425/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 425/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 425/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.854]
+Epoch 425/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.85] 
+Epoch 425/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.855]
+Epoch 425/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.854]
+Epoch 425/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.845]
+Epoch 425/10001:  50%|█████     | 5/10 [00:00<00:00, 10.55it/s, Loss=0.845]
+Epoch 425/10001:  50%|█████     | 5/10 [00:00<00:00, 10.55it/s, Loss=0.849]
+Epoch 425/10001:  50%|█████     | 5/10 [00:00<00:00, 10.55it/s, Loss=0.847]
+Epoch 425/10001:  50%|█████     | 5/10 [00:00<00:00, 10.55it/s, Loss=0.851]
+Epoch 425/10001:  50%|█████     | 5/10 [00:00<00:00, 10.55it/s, Loss=0.849]
+Epoch 425/10001:  50%|█████     | 5/10 [00:00<00:00, 10.55it/s, Loss=0.853]
+Epoch 425/10001: 100%|██████████| 10/10 [00:00<00:00, 12.71it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 426/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 426/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 426/10001:  10%|█         | 1/10 [00:00<00:04,  1.94it/s, Loss=0.853]
+Epoch 426/10001:  10%|█         | 1/10 [00:00<00:04,  1.94it/s, Loss=0.843]
+Epoch 426/10001:  10%|█         | 1/10 [00:00<00:04,  1.94it/s, Loss=0.856]
+Epoch 426/10001:  10%|█         | 1/10 [00:00<00:04,  1.94it/s, Loss=0.849]
+Epoch 426/10001:  10%|█         | 1/10 [00:00<00:04,  1.94it/s, Loss=0.854]
+Epoch 426/10001:  10%|█         | 1/10 [00:00<00:04,  1.94it/s, Loss=0.861]
+Epoch 426/10001:  60%|██████    | 6/10 [00:00<00:00, 11.99it/s, Loss=0.861]
+Epoch 426/10001:  60%|██████    | 6/10 [00:00<00:00, 11.99it/s, Loss=0.848]
+Epoch 426/10001:  60%|██████    | 6/10 [00:00<00:00, 11.99it/s, Loss=0.855]
+Epoch 426/10001:  60%|██████    | 6/10 [00:00<00:00, 11.99it/s, Loss=0.853]
+Epoch 426/10001:  60%|██████    | 6/10 [00:00<00:00, 11.99it/s, Loss=0.849]
+Epoch 426/10001: 100%|██████████| 10/10 [00:00<00:00, 12.28it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 427/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 427/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.841]
+Epoch 427/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.841]
+Epoch 427/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.853]
+Epoch 427/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.851]
+Epoch 427/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.856]
+Epoch 427/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.854]
+Epoch 427/10001:  50%|█████     | 5/10 [00:00<00:00, 11.71it/s, Loss=0.854]
+Epoch 427/10001:  50%|█████     | 5/10 [00:00<00:00, 11.71it/s, Loss=0.847]
+Epoch 427/10001:  50%|█████     | 5/10 [00:00<00:00, 11.71it/s, Loss=0.847]
+Epoch 427/10001:  50%|█████     | 5/10 [00:00<00:00, 11.71it/s, Loss=0.85] 
+Epoch 427/10001:  50%|█████     | 5/10 [00:00<00:00, 11.71it/s, Loss=0.851]
+Epoch 427/10001:  50%|█████     | 5/10 [00:00<00:00, 11.71it/s, Loss=0.855]
+Epoch 427/10001: 100%|██████████| 10/10 [00:00<00:00, 13.65it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 428/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 428/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 428/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.854]
+Epoch 428/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.849]
+Epoch 428/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.85] 
+Epoch 428/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.851]
+Epoch 428/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.851]
+Epoch 428/10001:  50%|█████     | 5/10 [00:00<00:00, 13.23it/s, Loss=0.851]
+Epoch 428/10001:  50%|█████     | 5/10 [00:00<00:00, 13.23it/s, Loss=0.848]
+Epoch 428/10001:  50%|█████     | 5/10 [00:00<00:00, 13.23it/s, Loss=0.859]
+Epoch 428/10001:  50%|█████     | 5/10 [00:00<00:00, 13.23it/s, Loss=0.854]
+Epoch 428/10001:  50%|█████     | 5/10 [00:00<00:00, 13.23it/s, Loss=0.855]
+Epoch 428/10001:  50%|█████     | 5/10 [00:00<00:00, 13.23it/s, Loss=0.853]
+Epoch 428/10001: 100%|██████████| 10/10 [00:00<00:00, 15.49it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 429/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 429/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 429/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.856]
+Epoch 429/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.847]
+Epoch 429/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.845]
+Epoch 429/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.856]
+Epoch 429/10001:  40%|████      | 4/10 [00:00<00:00, 10.55it/s, Loss=0.856]
+Epoch 429/10001:  40%|████      | 4/10 [00:00<00:00, 10.55it/s, Loss=0.857]
+Epoch 429/10001:  40%|████      | 4/10 [00:00<00:00, 10.55it/s, Loss=0.848]
+Epoch 429/10001:  40%|████      | 4/10 [00:00<00:00, 10.55it/s, Loss=0.853]
+Epoch 429/10001:  40%|████      | 4/10 [00:00<00:00, 10.55it/s, Loss=0.846]
+Epoch 429/10001:  80%|████████  | 8/10 [00:00<00:00, 18.35it/s, Loss=0.846]
+Epoch 429/10001:  80%|████████  | 8/10 [00:00<00:00, 18.35it/s, Loss=0.847]
+Epoch 429/10001:  80%|████████  | 8/10 [00:00<00:00, 18.35it/s, Loss=0.847]
+Epoch 429/10001: 100%|██████████| 10/10 [00:00<00:00, 12.85it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 430/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 430/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 430/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.855]
+Epoch 430/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.855]
+Epoch 430/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.853]
+Epoch 430/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.846]
+Epoch 430/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.848]
+Epoch 430/10001:  50%|█████     | 5/10 [00:00<00:00, 10.80it/s, Loss=0.848]
+Epoch 430/10001:  50%|█████     | 5/10 [00:00<00:00, 10.80it/s, Loss=0.85] 
+Epoch 430/10001:  50%|█████     | 5/10 [00:00<00:00, 10.80it/s, Loss=0.853]
+Epoch 430/10001:  50%|█████     | 5/10 [00:00<00:00, 10.80it/s, Loss=0.848]
+Epoch 430/10001:  50%|█████     | 5/10 [00:00<00:00, 10.80it/s, Loss=0.851]
+Epoch 430/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.48it/s, Loss=0.851]
+Epoch 430/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.48it/s, Loss=0.858]
+Epoch 430/10001: 100%|██████████| 10/10 [00:00<00:00, 12.05it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 431/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 431/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 431/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.853]
+Epoch 431/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.847]
+Epoch 431/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.851]
+Epoch 431/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.848]
+Epoch 431/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.851]
+Epoch 431/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.847]
+Epoch 431/10001:  60%|██████    | 6/10 [00:00<00:00, 14.21it/s, Loss=0.847]
+Epoch 431/10001:  60%|██████    | 6/10 [00:00<00:00, 14.21it/s, Loss=0.854]
+Epoch 431/10001:  60%|██████    | 6/10 [00:00<00:00, 14.21it/s, Loss=0.847]
+Epoch 431/10001:  60%|██████    | 6/10 [00:00<00:00, 14.21it/s, Loss=0.844]
+Epoch 431/10001:  60%|██████    | 6/10 [00:00<00:00, 14.21it/s, Loss=0.856]
+Epoch 431/10001: 100%|██████████| 10/10 [00:00<00:00, 20.31it/s, Loss=0.856]
+Epoch 431/10001: 100%|██████████| 10/10 [00:00<00:00, 13.15it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 432/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 432/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 432/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.847]
+Epoch 432/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.853]
+Epoch 432/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.857]
+Epoch 432/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.854]
+Epoch 432/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.852]
+Epoch 432/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.853]
+Epoch 432/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.853]
+Epoch 432/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.849]
+Epoch 432/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.856]
+Epoch 432/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.854]
+Epoch 432/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.851]
+Epoch 432/10001: 100%|██████████| 10/10 [00:00<00:00, 13.40it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 433/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 433/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 433/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.845]
+Epoch 433/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.845]
+Epoch 433/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.851]
+Epoch 433/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.848]
+Epoch 433/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.846]
+Epoch 433/10001:  50%|█████     | 5/10 [00:00<00:00, 10.26it/s, Loss=0.846]
+Epoch 433/10001:  50%|█████     | 5/10 [00:00<00:00, 10.26it/s, Loss=0.85] 
+Epoch 433/10001:  50%|█████     | 5/10 [00:00<00:00, 10.26it/s, Loss=0.847]
+Epoch 433/10001:  50%|█████     | 5/10 [00:00<00:00, 10.26it/s, Loss=0.856]
+Epoch 433/10001:  50%|█████     | 5/10 [00:00<00:00, 10.26it/s, Loss=0.849]
+Epoch 433/10001:  90%|█████████ | 9/10 [00:00<00:00, 16.99it/s, Loss=0.849]
+Epoch 433/10001:  90%|█████████ | 9/10 [00:00<00:00, 16.99it/s, Loss=0.857]
+Epoch 433/10001: 100%|██████████| 10/10 [00:00<00:00, 11.37it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 434/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 434/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 434/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.851]
+Epoch 434/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.851]
+Epoch 434/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.859]
+Epoch 434/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.851]
+Epoch 434/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.85] 
+Epoch 434/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.847]
+Epoch 434/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.847]
+Epoch 434/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.86] 
+Epoch 434/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.852]
+Epoch 434/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.851]
+Epoch 434/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.855]
+Epoch 434/10001: 100%|██████████| 10/10 [00:00<00:00, 12.85it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 435/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 435/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 435/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.854]
+Epoch 435/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.857]
+Epoch 435/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.858]
+Epoch 435/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.85] 
+Epoch 435/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.853]
+Epoch 435/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.854]
+Epoch 435/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.849]
+Epoch 435/10001:  70%|███████   | 7/10 [00:00<00:00, 20.26it/s, Loss=0.849]
+Epoch 435/10001:  70%|███████   | 7/10 [00:00<00:00, 20.26it/s, Loss=0.851]
+Epoch 435/10001:  70%|███████   | 7/10 [00:00<00:00, 20.26it/s, Loss=0.858]
+Epoch 435/10001:  70%|███████   | 7/10 [00:00<00:00, 20.26it/s, Loss=0.855]
+Epoch 435/10001: 100%|██████████| 10/10 [00:00<00:00, 17.25it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 436/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 436/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 436/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.851]
+Epoch 436/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.854]
+Epoch 436/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.858]
+Epoch 436/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.843]
+Epoch 436/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.849]
+Epoch 436/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.849]
+Epoch 436/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.849]
+Epoch 436/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.852]
+Epoch 436/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.855]
+Epoch 436/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.846]
+Epoch 436/10001:  50%|█████     | 5/10 [00:00<00:00, 11.50it/s, Loss=0.853]
+Epoch 436/10001: 100%|██████████| 10/10 [00:00<00:00, 13.78it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 437/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 437/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 437/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.848]
+Epoch 437/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.84] 
+Epoch 437/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.853]
+Epoch 437/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.856]
+Epoch 437/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.85] 
+Epoch 437/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.858]
+Epoch 437/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.858]
+Epoch 437/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.85] 
+Epoch 437/10001:  80%|████████  | 8/10 [00:00<00:00, 20.34it/s, Loss=0.85]
+Epoch 437/10001:  80%|████████  | 8/10 [00:00<00:00, 20.34it/s, Loss=0.845]
+Epoch 437/10001:  80%|████████  | 8/10 [00:00<00:00, 20.34it/s, Loss=0.853]
+Epoch 437/10001: 100%|██████████| 10/10 [00:00<00:00, 16.09it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 438/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 438/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 438/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.852]
+Epoch 438/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.855]
+Epoch 438/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.843]
+Epoch 438/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.845]
+Epoch 438/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.846]
+Epoch 438/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.849]
+Epoch 438/10001:  60%|██████    | 6/10 [00:00<00:00, 14.20it/s, Loss=0.849]
+Epoch 438/10001:  60%|██████    | 6/10 [00:00<00:00, 14.20it/s, Loss=0.846]
+Epoch 438/10001:  60%|██████    | 6/10 [00:00<00:00, 14.20it/s, Loss=0.845]
+Epoch 438/10001:  60%|██████    | 6/10 [00:00<00:00, 14.20it/s, Loss=0.848]
+Epoch 438/10001:  60%|██████    | 6/10 [00:00<00:00, 14.20it/s, Loss=0.847]
+Epoch 438/10001: 100%|██████████| 10/10 [00:00<00:00, 14.48it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 439/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 439/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 439/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.858]
+Epoch 439/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.851]
+Epoch 439/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.854]
+Epoch 439/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.848]
+Epoch 439/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.843]
+Epoch 439/10001:  10%|█         | 1/10 [00:00<00:03,  2.73it/s, Loss=0.851]
+Epoch 439/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.851]
+Epoch 439/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.856]
+Epoch 439/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.859]
+Epoch 439/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.846]
+Epoch 439/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.846]
+Epoch 439/10001: 100%|██████████| 10/10 [00:00<00:00, 14.70it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 440/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 440/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 440/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.845]
+Epoch 440/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.858]
+Epoch 440/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.845]
+Epoch 440/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.859]
+Epoch 440/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.86] 
+Epoch 440/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.86]
+Epoch 440/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.847]
+Epoch 440/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.847]
+Epoch 440/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.847]
+Epoch 440/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.847]
+Epoch 440/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.19it/s, Loss=0.847]
+Epoch 440/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.19it/s, Loss=0.845]
+Epoch 440/10001: 100%|██████████| 10/10 [00:00<00:00, 12.51it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 441/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 441/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 441/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.856]
+Epoch 441/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.855]
+Epoch 441/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.843]
+Epoch 441/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.848]
+Epoch 441/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.847]
+Epoch 441/10001:  50%|█████     | 5/10 [00:00<00:00, 11.86it/s, Loss=0.847]
+Epoch 441/10001:  50%|█████     | 5/10 [00:00<00:00, 11.86it/s, Loss=0.847]
+Epoch 441/10001:  50%|█████     | 5/10 [00:00<00:00, 11.86it/s, Loss=0.853]
+Epoch 441/10001:  50%|█████     | 5/10 [00:00<00:00, 11.86it/s, Loss=0.857]
+Epoch 441/10001:  50%|█████     | 5/10 [00:00<00:00, 11.86it/s, Loss=0.849]
+Epoch 441/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.90it/s, Loss=0.849]
+Epoch 441/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.90it/s, Loss=0.854]
+Epoch 441/10001: 100%|██████████| 10/10 [00:00<00:00, 13.03it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 442/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 442/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 442/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.858]
+Epoch 442/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.847]
+Epoch 442/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.845]
+Epoch 442/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.847]
+Epoch 442/10001:  10%|█         | 1/10 [00:00<00:03,  2.60it/s, Loss=0.851]
+Epoch 442/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.851]
+Epoch 442/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.849]
+Epoch 442/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.85] 
+Epoch 442/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.857]
+Epoch 442/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.85] 
+Epoch 442/10001:  50%|█████     | 5/10 [00:00<00:00, 12.67it/s, Loss=0.854]
+Epoch 442/10001: 100%|██████████| 10/10 [00:00<00:00, 14.05it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 443/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 443/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 443/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.848]
+Epoch 443/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.848]
+Epoch 443/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 443/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 443/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 443/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 443/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.847]
+Epoch 443/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.856]
+Epoch 443/10001:  80%|████████  | 8/10 [00:00<00:00, 17.93it/s, Loss=0.856]
+Epoch 443/10001:  80%|████████  | 8/10 [00:00<00:00, 17.93it/s, Loss=0.851]
+Epoch 443/10001:  80%|████████  | 8/10 [00:00<00:00, 17.93it/s, Loss=0.85] 
+Epoch 443/10001: 100%|██████████| 10/10 [00:00<00:00, 14.03it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 444/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 444/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 444/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.854]
+Epoch 444/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.852]
+Epoch 444/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.855]
+Epoch 444/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.849]
+Epoch 444/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 444/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.855]
+Epoch 444/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.855]
+Epoch 444/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.85] 
+Epoch 444/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.849]
+Epoch 444/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.852]
+Epoch 444/10001:  60%|██████    | 6/10 [00:00<00:00, 13.50it/s, Loss=0.853]
+Epoch 444/10001: 100%|██████████| 10/10 [00:00<00:00, 13.16it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 445/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 445/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 445/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.854]
+Epoch 445/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.852]
+Epoch 445/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.854]
+Epoch 445/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.843]
+Epoch 445/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.851]
+Epoch 445/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.85] 
+Epoch 445/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.845]
+Epoch 445/10001:  70%|███████   | 7/10 [00:00<00:00, 17.51it/s, Loss=0.845]
+Epoch 445/10001:  70%|███████   | 7/10 [00:00<00:00, 17.51it/s, Loss=0.847]
+Epoch 445/10001:  70%|███████   | 7/10 [00:00<00:00, 17.51it/s, Loss=0.853]
+Epoch 445/10001:  70%|███████   | 7/10 [00:00<00:00, 17.51it/s, Loss=0.849]
+Epoch 445/10001: 100%|██████████| 10/10 [00:00<00:00, 14.44it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 446/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 446/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.844]
+Epoch 446/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.844]
+Epoch 446/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.85] 
+Epoch 446/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.852]
+Epoch 446/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.856]
+Epoch 446/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.85] 
+Epoch 446/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.849]
+Epoch 446/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.849]
+Epoch 446/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.857]
+Epoch 446/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.854]
+Epoch 446/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.849]
+Epoch 446/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.85] 
+Epoch 446/10001: 100%|██████████| 10/10 [00:00<00:00, 14.36it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 447/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 447/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 447/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.854]
+Epoch 447/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.857]
+Epoch 447/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.852]
+Epoch 447/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.86] 
+Epoch 447/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.845]
+Epoch 447/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.851]
+Epoch 447/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.851]
+Epoch 447/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.849]
+Epoch 447/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.853]
+Epoch 447/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.843]
+Epoch 447/10001:  60%|██████    | 6/10 [00:00<00:00, 15.80it/s, Loss=0.85] 
+Epoch 447/10001: 100%|██████████| 10/10 [00:00<00:00, 22.09it/s, Loss=0.85]
+Epoch 447/10001: 100%|██████████| 10/10 [00:00<00:00, 13.85it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 448/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 448/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 448/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.848]
+Epoch 448/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.846]
+Epoch 448/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.847]
+Epoch 448/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.849]
+Epoch 448/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.845]
+Epoch 448/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.845]
+Epoch 448/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.852]
+Epoch 448/10001:  70%|███████   | 7/10 [00:00<00:00, 16.93it/s, Loss=0.852]
+Epoch 448/10001:  70%|███████   | 7/10 [00:00<00:00, 16.93it/s, Loss=0.847]
+Epoch 448/10001:  70%|███████   | 7/10 [00:00<00:00, 16.93it/s, Loss=0.854]
+Epoch 448/10001:  70%|███████   | 7/10 [00:00<00:00, 16.93it/s, Loss=0.851]
+Epoch 448/10001: 100%|██████████| 10/10 [00:00<00:00, 14.60it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 449/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 449/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 449/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.847]
+Epoch 449/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.857]
+Epoch 449/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.85] 
+Epoch 449/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.85]
+Epoch 449/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.852]
+Epoch 449/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.843]
+Epoch 449/10001:  60%|██████    | 6/10 [00:00<00:00, 12.10it/s, Loss=0.843]
+Epoch 449/10001:  60%|██████    | 6/10 [00:00<00:00, 12.10it/s, Loss=0.851]
+Epoch 449/10001:  60%|██████    | 6/10 [00:00<00:00, 12.10it/s, Loss=0.859]
+Epoch 449/10001:  60%|██████    | 6/10 [00:00<00:00, 12.10it/s, Loss=0.854]
+Epoch 449/10001:  60%|██████    | 6/10 [00:00<00:00, 12.10it/s, Loss=0.851]
+Epoch 449/10001: 100%|██████████| 10/10 [00:00<00:00, 12.46it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 450/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 450/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 450/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 450/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.855]
+Epoch 450/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.843]
+Epoch 450/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.848]
+Epoch 450/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.845]
+Epoch 450/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.848]
+Epoch 450/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.848]
+Epoch 450/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.853]
+Epoch 450/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.853]
+Epoch 450/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.846]
+Epoch 450/10001:  60%|██████    | 6/10 [00:00<00:00, 13.94it/s, Loss=0.848]
+Epoch 450/10001: 100%|██████████| 10/10 [00:00<00:00, 13.48it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 451/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 451/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 451/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.853]
+Epoch 451/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.852]
+Epoch 451/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.858]
+Epoch 451/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.848]
+Epoch 451/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.856]
+Epoch 451/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.858]
+Epoch 451/10001:  60%|██████    | 6/10 [00:00<00:00, 14.73it/s, Loss=0.858]
+Epoch 451/10001:  60%|██████    | 6/10 [00:00<00:00, 14.73it/s, Loss=0.852]
+Epoch 451/10001:  60%|██████    | 6/10 [00:00<00:00, 14.73it/s, Loss=0.847]
+Epoch 451/10001:  60%|██████    | 6/10 [00:00<00:00, 14.73it/s, Loss=0.851]
+Epoch 451/10001:  60%|██████    | 6/10 [00:00<00:00, 14.73it/s, Loss=0.847]
+Epoch 451/10001: 100%|██████████| 10/10 [00:00<00:00, 13.72it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 452/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 452/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 452/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.849]
+Epoch 452/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.847]
+Epoch 452/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.846]
+Epoch 452/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.857]
+Epoch 452/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.85] 
+Epoch 452/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.863]
+Epoch 452/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.849]
+Epoch 452/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.857]
+Epoch 452/10001:  80%|████████  | 8/10 [00:00<00:00, 18.16it/s, Loss=0.857]
+Epoch 452/10001:  80%|████████  | 8/10 [00:00<00:00, 18.16it/s, Loss=0.845]
+Epoch 452/10001:  80%|████████  | 8/10 [00:00<00:00, 18.16it/s, Loss=0.854]
+Epoch 452/10001: 100%|██████████| 10/10 [00:00<00:00, 13.74it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 453/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 453/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 453/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.854]
+Epoch 453/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.846]
+Epoch 453/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.844]
+Epoch 453/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.852]
+Epoch 453/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.856]
+Epoch 453/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.848]
+Epoch 453/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.85] 
+Epoch 453/10001:  70%|███████   | 7/10 [00:00<00:00, 15.35it/s, Loss=0.85]
+Epoch 453/10001:  70%|███████   | 7/10 [00:00<00:00, 15.35it/s, Loss=0.852]
+Epoch 453/10001:  70%|███████   | 7/10 [00:00<00:00, 15.35it/s, Loss=0.85] 
+Epoch 453/10001:  70%|███████   | 7/10 [00:00<00:00, 15.35it/s, Loss=0.852]
+Epoch 453/10001: 100%|██████████| 10/10 [00:00<00:00, 12.96it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 454/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 454/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 454/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.853]
+Epoch 454/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.846]
+Epoch 454/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.85] 
+Epoch 454/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.853]
+Epoch 454/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.844]
+Epoch 454/10001:  50%|█████     | 5/10 [00:00<00:00, 11.30it/s, Loss=0.844]
+Epoch 454/10001:  50%|█████     | 5/10 [00:00<00:00, 11.30it/s, Loss=0.848]
+Epoch 454/10001:  50%|█████     | 5/10 [00:00<00:00, 11.30it/s, Loss=0.846]
+Epoch 454/10001:  50%|█████     | 5/10 [00:00<00:00, 11.30it/s, Loss=0.85] 
+Epoch 454/10001:  50%|█████     | 5/10 [00:00<00:00, 11.30it/s, Loss=0.86]
+Epoch 454/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.23it/s, Loss=0.86]
+Epoch 454/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.23it/s, Loss=0.854]
+Epoch 454/10001: 100%|██████████| 10/10 [00:00<00:00, 12.30it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 455/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 455/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 455/10001:  10%|█         | 1/10 [00:00<00:02,  3.13it/s, Loss=0.853]
+Epoch 455/10001:  10%|█         | 1/10 [00:00<00:02,  3.13it/s, Loss=0.847]
+Epoch 455/10001:  10%|█         | 1/10 [00:00<00:02,  3.13it/s, Loss=0.855]
+Epoch 455/10001:  10%|█         | 1/10 [00:00<00:02,  3.13it/s, Loss=0.847]
+Epoch 455/10001:  10%|█         | 1/10 [00:00<00:02,  3.13it/s, Loss=0.847]
+Epoch 455/10001:  10%|█         | 1/10 [00:00<00:02,  3.13it/s, Loss=0.848]
+Epoch 455/10001:  60%|██████    | 6/10 [00:00<00:00, 17.28it/s, Loss=0.848]
+Epoch 455/10001:  60%|██████    | 6/10 [00:00<00:00, 17.28it/s, Loss=0.849]
+Epoch 455/10001:  60%|██████    | 6/10 [00:00<00:00, 17.28it/s, Loss=0.856]
+Epoch 455/10001:  60%|██████    | 6/10 [00:00<00:00, 17.28it/s, Loss=0.849]
+Epoch 455/10001:  60%|██████    | 6/10 [00:00<00:00, 17.28it/s, Loss=0.853]
+Epoch 455/10001: 100%|██████████| 10/10 [00:00<00:00, 15.61it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 456/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 456/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 456/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.855]
+Epoch 456/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.846]
+Epoch 456/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.854]
+Epoch 456/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.862]
+Epoch 456/10001:  10%|█         | 1/10 [00:00<00:04,  2.09it/s, Loss=0.855]
+Epoch 456/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.855]
+Epoch 456/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.849]
+Epoch 456/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.852]
+Epoch 456/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.851]
+Epoch 456/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.849]
+Epoch 456/10001:  50%|█████     | 5/10 [00:00<00:00, 10.47it/s, Loss=0.852]
+Epoch 456/10001: 100%|██████████| 10/10 [00:00<00:00, 19.47it/s, Loss=0.852]
+Epoch 456/10001: 100%|██████████| 10/10 [00:00<00:00, 12.24it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 457/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 457/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 457/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.853]
+Epoch 457/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.853]
+Epoch 457/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.852]
+Epoch 457/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.856]
+Epoch 457/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.852]
+Epoch 457/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.856]
+Epoch 457/10001:  60%|██████    | 6/10 [00:00<00:00, 13.11it/s, Loss=0.856]
+Epoch 457/10001:  60%|██████    | 6/10 [00:00<00:00, 13.11it/s, Loss=0.85] 
+Epoch 457/10001:  60%|██████    | 6/10 [00:00<00:00, 13.11it/s, Loss=0.849]
+Epoch 457/10001:  60%|██████    | 6/10 [00:00<00:00, 13.11it/s, Loss=0.848]
+Epoch 457/10001:  60%|██████    | 6/10 [00:00<00:00, 13.11it/s, Loss=0.849]
+Epoch 457/10001: 100%|██████████| 10/10 [00:00<00:00, 12.97it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 458/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 458/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 458/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.853]
+Epoch 458/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.851]
+Epoch 458/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.846]
+Epoch 458/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 458/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.853]
+Epoch 458/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.853]
+Epoch 458/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.847]
+Epoch 458/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.855]
+Epoch 458/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.85] 
+Epoch 458/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.847]
+Epoch 458/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.843]
+Epoch 458/10001: 100%|██████████| 10/10 [00:00<00:00, 20.33it/s, Loss=0.843]
+Epoch 458/10001: 100%|██████████| 10/10 [00:00<00:00, 13.05it/s, Loss=0.843]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 459/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 459/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 459/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.848]
+Epoch 459/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.852]
+Epoch 459/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.846]
+Epoch 459/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.857]
+Epoch 459/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.856]
+Epoch 459/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.854]
+Epoch 459/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.846]
+Epoch 459/10001:  70%|███████   | 7/10 [00:00<00:00, 17.72it/s, Loss=0.846]
+Epoch 459/10001:  70%|███████   | 7/10 [00:00<00:00, 17.72it/s, Loss=0.848]
+Epoch 459/10001:  70%|███████   | 7/10 [00:00<00:00, 17.72it/s, Loss=0.854]
+Epoch 459/10001:  70%|███████   | 7/10 [00:00<00:00, 17.72it/s, Loss=0.867]
+Epoch 459/10001: 100%|██████████| 10/10 [00:00<00:00, 15.04it/s, Loss=0.867]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 460/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 460/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 460/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.851]
+Epoch 460/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.856]
+Epoch 460/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.856]
+Epoch 460/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.858]
+Epoch 460/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 460/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.85] 
+Epoch 460/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.852]
+Epoch 460/10001:  70%|███████   | 7/10 [00:00<00:00, 16.26it/s, Loss=0.852]
+Epoch 460/10001:  70%|███████   | 7/10 [00:00<00:00, 16.26it/s, Loss=0.853]
+Epoch 460/10001:  70%|███████   | 7/10 [00:00<00:00, 16.26it/s, Loss=0.855]
+Epoch 460/10001:  70%|███████   | 7/10 [00:00<00:00, 16.26it/s, Loss=0.851]
+Epoch 460/10001: 100%|██████████| 10/10 [00:00<00:00, 14.22it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 461/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 461/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.844]
+Epoch 461/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.844]
+Epoch 461/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.849]
+Epoch 461/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.851]
+Epoch 461/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.857]
+Epoch 461/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.847]
+Epoch 461/10001:  50%|█████     | 5/10 [00:00<00:00, 10.89it/s, Loss=0.847]
+Epoch 461/10001:  50%|█████     | 5/10 [00:00<00:00, 10.89it/s, Loss=0.856]
+Epoch 461/10001:  50%|█████     | 5/10 [00:00<00:00, 10.89it/s, Loss=0.85] 
+Epoch 461/10001:  50%|█████     | 5/10 [00:00<00:00, 10.89it/s, Loss=0.844]
+Epoch 461/10001:  50%|█████     | 5/10 [00:00<00:00, 10.89it/s, Loss=0.848]
+Epoch 461/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.38it/s, Loss=0.848]
+Epoch 461/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.38it/s, Loss=0.848]
+Epoch 461/10001: 100%|██████████| 10/10 [00:00<00:00, 11.98it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 462/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 462/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 462/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.853]
+Epoch 462/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.855]
+Epoch 462/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.859]
+Epoch 462/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.853]
+Epoch 462/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.854]
+Epoch 462/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.852]
+Epoch 462/10001:  60%|██████    | 6/10 [00:00<00:00, 13.84it/s, Loss=0.852]
+Epoch 462/10001:  60%|██████    | 6/10 [00:00<00:00, 13.84it/s, Loss=0.851]
+Epoch 462/10001:  60%|██████    | 6/10 [00:00<00:00, 13.84it/s, Loss=0.847]
+Epoch 462/10001:  60%|██████    | 6/10 [00:00<00:00, 13.84it/s, Loss=0.849]
+Epoch 462/10001:  60%|██████    | 6/10 [00:00<00:00, 13.84it/s, Loss=0.846]
+Epoch 462/10001: 100%|██████████| 10/10 [00:00<00:00, 13.46it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 463/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 463/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 463/10001:  10%|█         | 1/10 [00:00<00:04,  1.93it/s, Loss=0.854]
+Epoch 463/10001:  10%|█         | 1/10 [00:00<00:04,  1.93it/s, Loss=0.851]
+Epoch 463/10001:  10%|█         | 1/10 [00:00<00:04,  1.93it/s, Loss=0.85] 
+Epoch 463/10001:  10%|█         | 1/10 [00:00<00:04,  1.93it/s, Loss=0.849]
+Epoch 463/10001:  10%|█         | 1/10 [00:00<00:04,  1.93it/s, Loss=0.847]
+Epoch 463/10001:  10%|█         | 1/10 [00:00<00:04,  1.93it/s, Loss=0.853]
+Epoch 463/10001:  10%|█         | 1/10 [00:00<00:04,  1.93it/s, Loss=0.851]
+Epoch 463/10001:  70%|███████   | 7/10 [00:00<00:00, 13.96it/s, Loss=0.851]
+Epoch 463/10001:  70%|███████   | 7/10 [00:00<00:00, 13.96it/s, Loss=0.853]
+Epoch 463/10001:  70%|███████   | 7/10 [00:00<00:00, 13.96it/s, Loss=0.856]
+Epoch 463/10001:  70%|███████   | 7/10 [00:00<00:00, 13.96it/s, Loss=0.847]
+Epoch 463/10001: 100%|██████████| 10/10 [00:00<00:00, 12.23it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 464/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 464/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.839]
+Epoch 464/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.839]
+Epoch 464/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.856]
+Epoch 464/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.844]
+Epoch 464/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.846]
+Epoch 464/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.851]
+Epoch 464/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.851]
+Epoch 464/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.852]
+Epoch 464/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.855]
+Epoch 464/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.858]
+Epoch 464/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.863]
+Epoch 464/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.13it/s, Loss=0.863]
+Epoch 464/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.13it/s, Loss=0.842]
+Epoch 464/10001: 100%|██████████| 10/10 [00:00<00:00, 12.54it/s, Loss=0.842]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 465/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 465/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.852]
+Epoch 465/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.852]
+Epoch 465/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.856]
+Epoch 465/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.857]
+Epoch 465/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.853]
+Epoch 465/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.844]
+Epoch 465/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.851]
+Epoch 465/10001:  10%|█         | 1/10 [00:00<00:03,  2.97it/s, Loss=0.85] 
+Epoch 465/10001:  80%|████████  | 8/10 [00:00<00:00, 22.13it/s, Loss=0.85]
+Epoch 465/10001:  80%|████████  | 8/10 [00:00<00:00, 22.13it/s, Loss=0.848]
+Epoch 465/10001:  80%|████████  | 8/10 [00:00<00:00, 22.13it/s, Loss=0.853]
+Epoch 465/10001: 100%|██████████| 10/10 [00:00<00:00, 16.78it/s, Loss=0.853]
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+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 466/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.844]
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+Epoch 466/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.849]
+Epoch 466/10001:  70%|███████   | 7/10 [00:00<00:00, 16.51it/s, Loss=0.849]
+Epoch 466/10001:  70%|███████   | 7/10 [00:00<00:00, 16.51it/s, Loss=0.848]
+Epoch 466/10001:  70%|███████   | 7/10 [00:00<00:00, 16.51it/s, Loss=0.845]
+Epoch 466/10001:  70%|███████   | 7/10 [00:00<00:00, 16.51it/s, Loss=0.862]
+Epoch 466/10001: 100%|██████████| 10/10 [00:00<00:00, 14.32it/s, Loss=0.862]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 467/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.852]
+Epoch 467/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.863]
+Epoch 467/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.845]
+Epoch 467/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.851]
+Epoch 467/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.851]
+Epoch 467/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.848]
+Epoch 467/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.852]
+Epoch 467/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.851]
+Epoch 467/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.852]
+Epoch 467/10001:  50%|█████     | 5/10 [00:00<00:00, 11.65it/s, Loss=0.846]
+Epoch 467/10001: 100%|██████████| 10/10 [00:00<00:00, 13.41it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 468/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 468/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 468/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.855]
+Epoch 468/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.841]
+Epoch 468/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.855]
+Epoch 468/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.859]
+Epoch 468/10001:  10%|█         | 1/10 [00:00<00:03,  2.54it/s, Loss=0.849]
+Epoch 468/10001:  50%|█████     | 5/10 [00:00<00:00, 11.79it/s, Loss=0.849]
+Epoch 468/10001:  50%|█████     | 5/10 [00:00<00:00, 11.79it/s, Loss=0.853]
+Epoch 468/10001:  50%|█████     | 5/10 [00:00<00:00, 11.79it/s, Loss=0.846]
+Epoch 468/10001:  50%|█████     | 5/10 [00:00<00:00, 11.79it/s, Loss=0.849]
+Epoch 468/10001:  50%|█████     | 5/10 [00:00<00:00, 11.79it/s, Loss=0.85] 
+Epoch 468/10001:  50%|█████     | 5/10 [00:00<00:00, 11.79it/s, Loss=0.852]
+Epoch 468/10001: 100%|██████████| 10/10 [00:00<00:00, 13.27it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 469/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 469/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 469/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.852]
+Epoch 469/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 469/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.859]
+Epoch 469/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.85] 
+Epoch 469/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 469/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.851]
+Epoch 469/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.855]
+Epoch 469/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.853]
+Epoch 469/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.857]
+Epoch 469/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.842]
+Epoch 469/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.10it/s, Loss=0.842]
+Epoch 469/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.10it/s, Loss=0.846]
+Epoch 469/10001: 100%|██████████| 10/10 [00:00<00:00, 12.71it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
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+Epoch 470/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.851]
+Epoch 470/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.858]
+Epoch 470/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.852]
+Epoch 470/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.843]
+Epoch 470/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.848]
+Epoch 470/10001:  50%|█████     | 5/10 [00:00<00:00, 11.18it/s, Loss=0.851]
+Epoch 470/10001: 100%|██████████| 10/10 [00:00<00:00, 20.33it/s, Loss=0.851]
+Epoch 470/10001: 100%|██████████| 10/10 [00:00<00:00, 12.97it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 471/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 471/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 471/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.851]
+Epoch 471/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.851]
+Epoch 471/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.847]
+Epoch 471/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.848]
+Epoch 471/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.849]
+Epoch 471/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.849]
+Epoch 471/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.849]
+Epoch 471/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.853]
+Epoch 471/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.844]
+Epoch 471/10001:  50%|█████     | 5/10 [00:00<00:00, 11.26it/s, Loss=0.854]
+Epoch 471/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.48it/s, Loss=0.854]
+Epoch 471/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.48it/s, Loss=0.858]
+Epoch 471/10001: 100%|██████████| 10/10 [00:00<00:00, 12.22it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 472/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 472/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 472/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.85]
+Epoch 472/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.856]
+Epoch 472/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.849]
+Epoch 472/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.842]
+Epoch 472/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.86] 
+Epoch 472/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.851]
+Epoch 472/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.851]
+Epoch 472/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.85] 
+Epoch 472/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.855]
+Epoch 472/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.849]
+Epoch 472/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.847]
+Epoch 472/10001: 100%|██████████| 10/10 [00:00<00:00, 12.77it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 473/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 473/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.844]
+Epoch 473/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.844]
+Epoch 473/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.839]
+Epoch 473/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.85] 
+Epoch 473/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.845]
+Epoch 473/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.855]
+Epoch 473/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.852]
+Epoch 473/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.842]
+Epoch 473/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.849]
+Epoch 473/10001:  80%|████████  | 8/10 [00:00<00:00, 18.86it/s, Loss=0.849]
+Epoch 473/10001:  80%|████████  | 8/10 [00:00<00:00, 18.86it/s, Loss=0.851]
+Epoch 473/10001:  80%|████████  | 8/10 [00:00<00:00, 18.86it/s, Loss=0.853]
+Epoch 473/10001: 100%|██████████| 10/10 [00:00<00:00, 14.59it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 474/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 474/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 474/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.855]
+Epoch 474/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.853]
+Epoch 474/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.853]
+Epoch 474/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.845]
+Epoch 474/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.845]
+Epoch 474/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.845]
+Epoch 474/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.85] 
+Epoch 474/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.853]
+Epoch 474/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.856]
+Epoch 474/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.847]
+Epoch 474/10001:  50%|█████     | 5/10 [00:00<00:00, 11.83it/s, Loss=0.853]
+Epoch 474/10001: 100%|██████████| 10/10 [00:00<00:00, 21.08it/s, Loss=0.853]
+Epoch 474/10001: 100%|██████████| 10/10 [00:00<00:00, 13.31it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 475/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 475/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 475/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.853]
+Epoch 475/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.852]
+Epoch 475/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.854]
+Epoch 475/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.853]
+Epoch 475/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.857]
+Epoch 475/10001:  50%|█████     | 5/10 [00:00<00:00, 10.06it/s, Loss=0.857]
+Epoch 475/10001:  50%|█████     | 5/10 [00:00<00:00, 10.06it/s, Loss=0.849]
+Epoch 475/10001:  50%|█████     | 5/10 [00:00<00:00, 10.06it/s, Loss=0.858]
+Epoch 475/10001:  50%|█████     | 5/10 [00:00<00:00, 10.06it/s, Loss=0.848]
+Epoch 475/10001:  50%|█████     | 5/10 [00:00<00:00, 10.06it/s, Loss=0.855]
+Epoch 475/10001:  90%|█████████ | 9/10 [00:00<00:00, 16.90it/s, Loss=0.855]
+Epoch 475/10001:  90%|█████████ | 9/10 [00:00<00:00, 16.90it/s, Loss=0.854]
+Epoch 475/10001: 100%|██████████| 10/10 [00:00<00:00, 11.58it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 476/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 476/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 476/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 476/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.849]
+Epoch 476/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.848]
+Epoch 476/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.852]
+Epoch 476/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 476/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.856]
+Epoch 476/10001:  60%|██████    | 6/10 [00:00<00:00, 14.15it/s, Loss=0.856]
+Epoch 476/10001:  60%|██████    | 6/10 [00:00<00:00, 14.15it/s, Loss=0.855]
+Epoch 476/10001:  60%|██████    | 6/10 [00:00<00:00, 14.15it/s, Loss=0.859]
+Epoch 476/10001:  60%|██████    | 6/10 [00:00<00:00, 14.15it/s, Loss=0.858]
+Epoch 476/10001:  60%|██████    | 6/10 [00:00<00:00, 14.15it/s, Loss=0.849]
+Epoch 476/10001: 100%|██████████| 10/10 [00:00<00:00, 13.30it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 477/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 477/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 477/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.85]
+Epoch 477/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.853]
+Epoch 477/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.852]
+Epoch 477/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.856]
+Epoch 477/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.852]
+Epoch 477/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.852]
+Epoch 477/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.854]
+Epoch 477/10001:  70%|███████   | 7/10 [00:00<00:00, 15.85it/s, Loss=0.854]
+Epoch 477/10001:  70%|███████   | 7/10 [00:00<00:00, 15.85it/s, Loss=0.857]
+Epoch 477/10001:  70%|███████   | 7/10 [00:00<00:00, 15.85it/s, Loss=0.856]
+Epoch 477/10001:  70%|███████   | 7/10 [00:00<00:00, 15.85it/s, Loss=0.861]
+Epoch 477/10001: 100%|██████████| 10/10 [00:00<00:00, 13.50it/s, Loss=0.861]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 478/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 478/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 478/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.852]
+Epoch 478/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.852]
+Epoch 478/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.844]
+Epoch 478/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.855]
+Epoch 478/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.855]
+Epoch 478/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.851]
+Epoch 478/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.851]
+Epoch 478/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.851]
+Epoch 478/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.848]
+Epoch 478/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.851]
+Epoch 478/10001:  60%|██████    | 6/10 [00:00<00:00, 13.75it/s, Loss=0.854]
+Epoch 478/10001: 100%|██████████| 10/10 [00:00<00:00, 20.28it/s, Loss=0.854]
+Epoch 478/10001: 100%|██████████| 10/10 [00:00<00:00, 13.11it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 479/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 479/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 479/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.848]
+Epoch 479/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.847]
+Epoch 479/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.849]
+Epoch 479/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.854]
+Epoch 479/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.852]
+Epoch 479/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.843]
+Epoch 479/10001:  60%|██████    | 6/10 [00:00<00:00, 15.16it/s, Loss=0.843]
+Epoch 479/10001:  60%|██████    | 6/10 [00:00<00:00, 15.16it/s, Loss=0.864]
+Epoch 479/10001:  60%|██████    | 6/10 [00:00<00:00, 15.16it/s, Loss=0.855]
+Epoch 479/10001:  60%|██████    | 6/10 [00:00<00:00, 15.16it/s, Loss=0.852]
+Epoch 479/10001:  60%|██████    | 6/10 [00:00<00:00, 15.16it/s, Loss=0.847]
+Epoch 479/10001: 100%|██████████| 10/10 [00:00<00:00, 14.85it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 480/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 480/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 480/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.848]
+Epoch 480/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.851]
+Epoch 480/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.853]
+Epoch 480/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.854]
+Epoch 480/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.85] 
+Epoch 480/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.855]
+Epoch 480/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.855]
+Epoch 480/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.849]
+Epoch 480/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.848]
+Epoch 480/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.849]
+Epoch 480/10001:  60%|██████    | 6/10 [00:00<00:00, 13.78it/s, Loss=0.851]
+Epoch 480/10001: 100%|██████████| 10/10 [00:00<00:00, 13.84it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 481/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 481/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 481/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.85]
+Epoch 481/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.855]
+Epoch 481/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.854]
+Epoch 481/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.854]
+Epoch 481/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.852]
+Epoch 481/10001:  10%|█         | 1/10 [00:00<00:03,  2.53it/s, Loss=0.849]
+Epoch 481/10001:  60%|██████    | 6/10 [00:00<00:00, 15.00it/s, Loss=0.849]
+Epoch 481/10001:  60%|██████    | 6/10 [00:00<00:00, 15.00it/s, Loss=0.851]
+Epoch 481/10001:  60%|██████    | 6/10 [00:00<00:00, 15.00it/s, Loss=0.853]
+Epoch 481/10001:  60%|██████    | 6/10 [00:00<00:00, 15.00it/s, Loss=0.851]
+Epoch 481/10001:  60%|██████    | 6/10 [00:00<00:00, 15.00it/s, Loss=0.851]
+Epoch 481/10001: 100%|██████████| 10/10 [00:00<00:00, 14.36it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 482/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 482/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 482/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.855]
+Epoch 482/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.857]
+Epoch 482/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.848]
+Epoch 482/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.846]
+Epoch 482/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.849]
+Epoch 482/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.852]
+Epoch 482/10001:  60%|██████    | 6/10 [00:00<00:00, 14.00it/s, Loss=0.852]
+Epoch 482/10001:  60%|██████    | 6/10 [00:00<00:00, 14.00it/s, Loss=0.851]
+Epoch 482/10001:  60%|██████    | 6/10 [00:00<00:00, 14.00it/s, Loss=0.851]
+Epoch 482/10001:  60%|██████    | 6/10 [00:00<00:00, 14.00it/s, Loss=0.848]
+Epoch 482/10001:  60%|██████    | 6/10 [00:00<00:00, 14.00it/s, Loss=0.849]
+Epoch 482/10001: 100%|██████████| 10/10 [00:00<00:00, 14.12it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 483/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 483/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 483/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.855]
+Epoch 483/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.845]
+Epoch 483/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.854]
+Epoch 483/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.856]
+Epoch 483/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.849]
+Epoch 483/10001:  50%|█████     | 5/10 [00:00<00:00, 10.75it/s, Loss=0.849]
+Epoch 483/10001:  50%|█████     | 5/10 [00:00<00:00, 10.75it/s, Loss=0.855]
+Epoch 483/10001:  50%|█████     | 5/10 [00:00<00:00, 10.75it/s, Loss=0.856]
+Epoch 483/10001:  50%|█████     | 5/10 [00:00<00:00, 10.75it/s, Loss=0.843]
+Epoch 483/10001:  50%|█████     | 5/10 [00:00<00:00, 10.75it/s, Loss=0.855]
+Epoch 483/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.77it/s, Loss=0.855]
+Epoch 483/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.77it/s, Loss=0.854]
+Epoch 483/10001: 100%|██████████| 10/10 [00:00<00:00, 12.45it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 484/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 484/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 484/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.843]
+Epoch 484/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.852]
+Epoch 484/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.849]
+Epoch 484/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.852]
+Epoch 484/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.85] 
+Epoch 484/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.851]
+Epoch 484/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.851]
+Epoch 484/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.854]
+Epoch 484/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.847]
+Epoch 484/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.85] 
+Epoch 484/10001:  60%|██████    | 6/10 [00:00<00:00, 14.38it/s, Loss=0.86]
+Epoch 484/10001: 100%|██████████| 10/10 [00:00<00:00, 20.57it/s, Loss=0.86]
+Epoch 484/10001: 100%|██████████| 10/10 [00:00<00:00, 12.98it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 485/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 485/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 485/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.845]
+Epoch 485/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.842]
+Epoch 485/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.85] 
+Epoch 485/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.85]
+Epoch 485/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.855]
+Epoch 485/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.849]
+Epoch 485/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.857]
+Epoch 485/10001:  70%|███████   | 7/10 [00:00<00:00, 15.65it/s, Loss=0.857]
+Epoch 485/10001:  70%|███████   | 7/10 [00:00<00:00, 15.65it/s, Loss=0.851]
+Epoch 485/10001:  70%|███████   | 7/10 [00:00<00:00, 15.65it/s, Loss=0.855]
+Epoch 485/10001:  70%|███████   | 7/10 [00:00<00:00, 15.65it/s, Loss=0.858]
+Epoch 485/10001: 100%|██████████| 10/10 [00:00<00:00, 13.57it/s, Loss=0.858]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 486/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 486/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 486/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.854]
+Epoch 486/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.844]
+Epoch 486/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.848]
+Epoch 486/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.847]
+Epoch 486/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.849]
+Epoch 486/10001:  50%|█████     | 5/10 [00:00<00:00, 11.45it/s, Loss=0.849]
+Epoch 486/10001:  50%|█████     | 5/10 [00:00<00:00, 11.45it/s, Loss=0.848]
+Epoch 486/10001:  50%|█████     | 5/10 [00:00<00:00, 11.45it/s, Loss=0.851]
+Epoch 486/10001:  50%|█████     | 5/10 [00:00<00:00, 11.45it/s, Loss=0.854]
+Epoch 486/10001:  50%|█████     | 5/10 [00:00<00:00, 11.45it/s, Loss=0.85] 
+Epoch 486/10001:  50%|█████     | 5/10 [00:00<00:00, 11.45it/s, Loss=0.851]
+Epoch 486/10001: 100%|██████████| 10/10 [00:00<00:00, 20.76it/s, Loss=0.851]
+Epoch 486/10001: 100%|██████████| 10/10 [00:00<00:00, 13.05it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 487/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 487/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 487/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.851]
+Epoch 487/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.846]
+Epoch 487/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.847]
+Epoch 487/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.856]
+Epoch 487/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.85] 
+Epoch 487/10001:  10%|█         | 1/10 [00:00<00:03,  2.67it/s, Loss=0.857]
+Epoch 487/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.857]
+Epoch 487/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.852]
+Epoch 487/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.854]
+Epoch 487/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.854]
+Epoch 487/10001:  60%|██████    | 6/10 [00:00<00:00, 15.71it/s, Loss=0.848]
+Epoch 487/10001: 100%|██████████| 10/10 [00:00<00:00, 22.10it/s, Loss=0.848]
+Epoch 487/10001: 100%|██████████| 10/10 [00:00<00:00, 13.42it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 488/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 488/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 488/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.847]
+Epoch 488/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.857]
+Epoch 488/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.856]
+Epoch 488/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.847]
+Epoch 488/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.85] 
+Epoch 488/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.855]
+Epoch 488/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.855]
+Epoch 488/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.855]
+Epoch 488/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.853]
+Epoch 488/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.851]
+Epoch 488/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.852]
+Epoch 488/10001: 100%|██████████| 10/10 [00:00<00:00, 13.87it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 489/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 489/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 489/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.852]
+Epoch 489/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.841]
+Epoch 489/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.846]
+Epoch 489/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.845]
+Epoch 489/10001:  10%|█         | 1/10 [00:00<00:03,  2.51it/s, Loss=0.858]
+Epoch 489/10001:  50%|█████     | 5/10 [00:00<00:00, 11.69it/s, Loss=0.858]
+Epoch 489/10001:  50%|█████     | 5/10 [00:00<00:00, 11.69it/s, Loss=0.849]
+Epoch 489/10001:  50%|█████     | 5/10 [00:00<00:00, 11.69it/s, Loss=0.844]
+Epoch 489/10001:  50%|█████     | 5/10 [00:00<00:00, 11.69it/s, Loss=0.854]
+Epoch 489/10001:  50%|█████     | 5/10 [00:00<00:00, 11.69it/s, Loss=0.846]
+Epoch 489/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.49it/s, Loss=0.846]
+Epoch 489/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.49it/s, Loss=0.854]
+Epoch 489/10001: 100%|██████████| 10/10 [00:00<00:00, 13.12it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 490/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 490/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 490/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.848]
+Epoch 490/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.854]
+Epoch 490/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.847]
+Epoch 490/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.846]
+Epoch 490/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 490/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.847]
+Epoch 490/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.847]
+Epoch 490/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.855]
+Epoch 490/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.854]
+Epoch 490/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.846]
+Epoch 490/10001:  60%|██████    | 6/10 [00:00<00:00, 13.67it/s, Loss=0.86] 
+Epoch 490/10001: 100%|██████████| 10/10 [00:00<00:00, 13.62it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 491/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 491/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 491/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.852]
+Epoch 491/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.86] 
+Epoch 491/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.856]
+Epoch 491/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.853]
+Epoch 491/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.856]
+Epoch 491/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.848]
+Epoch 491/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.848]
+Epoch 491/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.855]
+Epoch 491/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.854]
+Epoch 491/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.853]
+Epoch 491/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.854]
+Epoch 491/10001: 100%|██████████| 10/10 [00:00<00:00, 13.26it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 492/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 492/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 492/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.855]
+Epoch 492/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.861]
+Epoch 492/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.858]
+Epoch 492/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.851]
+Epoch 492/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.849]
+Epoch 492/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.853]
+Epoch 492/10001:  10%|█         | 1/10 [00:00<00:03,  2.50it/s, Loss=0.85] 
+Epoch 492/10001:  70%|███████   | 7/10 [00:00<00:00, 17.39it/s, Loss=0.85]
+Epoch 492/10001:  70%|███████   | 7/10 [00:00<00:00, 17.39it/s, Loss=0.856]
+Epoch 492/10001:  70%|███████   | 7/10 [00:00<00:00, 17.39it/s, Loss=0.852]
+Epoch 492/10001:  70%|███████   | 7/10 [00:00<00:00, 17.39it/s, Loss=0.846]
+Epoch 492/10001: 100%|██████████| 10/10 [00:00<00:00, 13.46it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 493/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 493/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 493/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 493/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.847]
+Epoch 493/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.853]
+Epoch 493/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.85] 
+Epoch 493/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.855]
+Epoch 493/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 493/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.851]
+Epoch 493/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.858]
+Epoch 493/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.848]
+Epoch 493/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.851]
+Epoch 493/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.853]
+Epoch 493/10001: 100%|██████████| 10/10 [00:00<00:00, 13.83it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 494/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 494/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 494/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.858]
+Epoch 494/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.848]
+Epoch 494/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.848]
+Epoch 494/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.85] 
+Epoch 494/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.852]
+Epoch 494/10001:  50%|█████     | 5/10 [00:00<00:00, 12.08it/s, Loss=0.852]
+Epoch 494/10001:  50%|█████     | 5/10 [00:00<00:00, 12.08it/s, Loss=0.851]
+Epoch 494/10001:  50%|█████     | 5/10 [00:00<00:00, 12.08it/s, Loss=0.852]
+Epoch 494/10001:  50%|█████     | 5/10 [00:00<00:00, 12.08it/s, Loss=0.855]
+Epoch 494/10001:  50%|█████     | 5/10 [00:00<00:00, 12.08it/s, Loss=0.85] 
+Epoch 494/10001:  50%|█████     | 5/10 [00:00<00:00, 12.08it/s, Loss=0.856]
+Epoch 494/10001: 100%|██████████| 10/10 [00:00<00:00, 14.05it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 495/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 495/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 495/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.848]
+Epoch 495/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.853]
+Epoch 495/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.844]
+Epoch 495/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.853]
+Epoch 495/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.858]
+Epoch 495/10001:  10%|█         | 1/10 [00:00<00:02,  3.08it/s, Loss=0.845]
+Epoch 495/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.845]
+Epoch 495/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.853]
+Epoch 495/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.85] 
+Epoch 495/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.856]
+Epoch 495/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.854]
+Epoch 495/10001: 100%|██████████| 10/10 [00:00<00:00, 15.68it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 496/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 496/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 496/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.849]
+Epoch 496/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.848]
+Epoch 496/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.853]
+Epoch 496/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.855]
+Epoch 496/10001:  10%|█         | 1/10 [00:00<00:03,  2.62it/s, Loss=0.858]
+Epoch 496/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.858]
+Epoch 496/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.853]
+Epoch 496/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.855]
+Epoch 496/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.853]
+Epoch 496/10001:  50%|█████     | 5/10 [00:00<00:00, 11.87it/s, Loss=0.855]
+Epoch 496/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.46it/s, Loss=0.855]
+Epoch 496/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.46it/s, Loss=0.846]
+Epoch 496/10001: 100%|██████████| 10/10 [00:00<00:00, 13.13it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 497/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 497/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 497/10001:  10%|█         | 1/10 [00:00<00:05,  1.70it/s, Loss=0.847]
+Epoch 497/10001:  10%|█         | 1/10 [00:00<00:05,  1.70it/s, Loss=0.855]
+Epoch 497/10001:  10%|█         | 1/10 [00:00<00:05,  1.70it/s, Loss=0.854]
+Epoch 497/10001:  10%|█         | 1/10 [00:00<00:05,  1.70it/s, Loss=0.851]
+Epoch 497/10001:  10%|█         | 1/10 [00:00<00:05,  1.70it/s, Loss=0.854]
+Epoch 497/10001:  50%|█████     | 5/10 [00:00<00:00,  8.86it/s, Loss=0.854]
+Epoch 497/10001:  50%|█████     | 5/10 [00:00<00:00,  8.86it/s, Loss=0.846]
+Epoch 497/10001:  50%|█████     | 5/10 [00:00<00:00,  8.86it/s, Loss=0.85] 
+Epoch 497/10001:  50%|█████     | 5/10 [00:00<00:00,  8.86it/s, Loss=0.847]
+Epoch 497/10001:  50%|█████     | 5/10 [00:00<00:00,  8.86it/s, Loss=0.846]
+Epoch 497/10001:  50%|█████     | 5/10 [00:00<00:00,  8.86it/s, Loss=0.846]
+Epoch 497/10001: 100%|██████████| 10/10 [00:00<00:00, 17.11it/s, Loss=0.846]
+Epoch 497/10001: 100%|██████████| 10/10 [00:00<00:00, 10.69it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 498/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 498/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 498/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.847]
+Epoch 498/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.85] 
+Epoch 498/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.853]
+Epoch 498/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.85] 
+Epoch 498/10001:  40%|████      | 4/10 [00:00<00:00,  8.82it/s, Loss=0.85]
+Epoch 498/10001:  40%|████      | 4/10 [00:00<00:00,  8.82it/s, Loss=0.859]
+Epoch 498/10001:  40%|████      | 4/10 [00:00<00:00,  8.82it/s, Loss=0.853]
+Epoch 498/10001:  40%|████      | 4/10 [00:00<00:00,  8.82it/s, Loss=0.845]
+Epoch 498/10001:  40%|████      | 4/10 [00:00<00:00,  8.82it/s, Loss=0.853]
+Epoch 498/10001:  80%|████████  | 8/10 [00:00<00:00, 16.70it/s, Loss=0.853]
+Epoch 498/10001:  80%|████████  | 8/10 [00:00<00:00, 16.70it/s, Loss=0.847]
+Epoch 498/10001:  80%|████████  | 8/10 [00:00<00:00, 16.70it/s, Loss=0.844]
+Epoch 498/10001: 100%|██████████| 10/10 [00:00<00:00, 12.57it/s, Loss=0.844]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 499/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 499/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 499/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.85]
+Epoch 499/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.854]
+Epoch 499/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.849]
+Epoch 499/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.85] 
+Epoch 499/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.852]
+Epoch 499/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.852]
+Epoch 499/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.845]
+Epoch 499/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.858]
+Epoch 499/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.861]
+Epoch 499/10001:  50%|█████     | 5/10 [00:00<00:00, 11.37it/s, Loss=0.852]
+Epoch 499/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.44it/s, Loss=0.852]
+Epoch 499/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.44it/s, Loss=0.853]
+Epoch 499/10001: 100%|██████████| 10/10 [00:00<00:00, 12.57it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 500/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 500/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 500/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.852]
+Epoch 500/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.851]
+Epoch 500/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.845]
+Epoch 500/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.852]
+Epoch 500/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.848]
+Epoch 500/10001:  10%|█         | 1/10 [00:00<00:03,  2.44it/s, Loss=0.844]
+Epoch 500/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.844]
+Epoch 500/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.852]
+Epoch 500/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.859]
+Epoch 500/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.853]
+Epoch 500/10001:  60%|██████    | 6/10 [00:00<00:00, 14.54it/s, Loss=0.848]
+Epoch 500/10001: 100%|██████████| 10/10 [00:00<00:00, 21.10it/s, Loss=0.848]
+Epoch 500/10001: 100%|██████████| 10/10 [00:00<00:00, 13.48it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 501/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 501/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.862]
+Epoch 501/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.862]
+Epoch 501/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.853]
+Epoch 501/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.85] 
+Epoch 501/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.855]
+Epoch 501/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.859]
+Epoch 501/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.847]
+Epoch 501/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.847]
+Epoch 501/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.855]
+Epoch 501/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.854]
+Epoch 501/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.851]
+Epoch 501/10001:  60%|██████    | 6/10 [00:00<00:00, 13.82it/s, Loss=0.842]
+Epoch 501/10001: 100%|██████████| 10/10 [00:00<00:00, 13.28it/s, Loss=0.842]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 502/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 502/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 502/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.85]
+Epoch 502/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.853]
+Epoch 502/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.846]
+Epoch 502/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.845]
+Epoch 502/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.846]
+Epoch 502/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.858]
+Epoch 502/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.853]
+Epoch 502/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.85] 
+Epoch 502/10001:  10%|█         | 1/10 [00:00<00:03,  2.45it/s, Loss=0.854]
+Epoch 502/10001:  90%|█████████ | 9/10 [00:00<00:00, 22.18it/s, Loss=0.854]
+Epoch 502/10001:  90%|█████████ | 9/10 [00:00<00:00, 22.18it/s, Loss=0.848]
+Epoch 502/10001: 100%|██████████| 10/10 [00:00<00:00, 15.34it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 503/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 503/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 503/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.848]
+Epoch 503/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.848]
+Epoch 503/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.846]
+Epoch 503/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.845]
+Epoch 503/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.845]
+Epoch 503/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.856]
+Epoch 503/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.854]
+Epoch 503/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.845]
+Epoch 503/10001:  80%|████████  | 8/10 [00:00<00:00, 18.39it/s, Loss=0.845]
+Epoch 503/10001:  80%|████████  | 8/10 [00:00<00:00, 18.39it/s, Loss=0.855]
+Epoch 503/10001:  80%|████████  | 8/10 [00:00<00:00, 18.39it/s, Loss=0.85] 
+Epoch 503/10001: 100%|██████████| 10/10 [00:00<00:00, 14.16it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 504/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 504/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 504/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.85]
+Epoch 504/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.848]
+Epoch 504/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.855]
+Epoch 504/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.856]
+Epoch 504/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.848]
+Epoch 504/10001:  50%|█████     | 5/10 [00:00<00:00, 10.36it/s, Loss=0.848]
+Epoch 504/10001:  50%|█████     | 5/10 [00:00<00:00, 10.36it/s, Loss=0.854]
+Epoch 504/10001:  50%|█████     | 5/10 [00:00<00:00, 10.36it/s, Loss=0.847]
+Epoch 504/10001:  50%|█████     | 5/10 [00:00<00:00, 10.36it/s, Loss=0.847]
+Epoch 504/10001:  50%|█████     | 5/10 [00:00<00:00, 10.36it/s, Loss=0.853]
+Epoch 504/10001:  90%|█████████ | 9/10 [00:00<00:00, 16.79it/s, Loss=0.853]
+Epoch 504/10001:  90%|█████████ | 9/10 [00:00<00:00, 16.79it/s, Loss=0.854]
+Epoch 504/10001: 100%|██████████| 10/10 [00:00<00:00, 11.65it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 505/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 505/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 505/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.847]
+Epoch 505/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.849]
+Epoch 505/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.862]
+Epoch 505/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.847]
+Epoch 505/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.861]
+Epoch 505/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.851]
+Epoch 505/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.849]
+Epoch 505/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.841]
+Epoch 505/10001:  80%|████████  | 8/10 [00:00<00:00, 18.65it/s, Loss=0.841]
+Epoch 505/10001:  80%|████████  | 8/10 [00:00<00:00, 18.65it/s, Loss=0.847]
+Epoch 505/10001:  80%|████████  | 8/10 [00:00<00:00, 18.65it/s, Loss=0.854]
+Epoch 505/10001: 100%|██████████| 10/10 [00:00<00:00, 14.73it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 506/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 506/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 506/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.852]
+Epoch 506/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.856]
+Epoch 506/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.844]
+Epoch 506/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.847]
+Epoch 506/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.847]
+Epoch 506/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.85] 
+Epoch 506/10001:  10%|█         | 1/10 [00:00<00:03,  2.70it/s, Loss=0.851]
+Epoch 506/10001:  70%|███████   | 7/10 [00:00<00:00, 18.18it/s, Loss=0.851]
+Epoch 506/10001:  70%|███████   | 7/10 [00:00<00:00, 18.18it/s, Loss=0.852]
+Epoch 506/10001:  70%|███████   | 7/10 [00:00<00:00, 18.18it/s, Loss=0.85] 
+Epoch 506/10001:  70%|███████   | 7/10 [00:00<00:00, 18.18it/s, Loss=0.849]
+Epoch 506/10001: 100%|██████████| 10/10 [00:00<00:00, 16.08it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 507/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 507/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 507/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.851]
+Epoch 507/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.836]
+Epoch 507/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.856]
+Epoch 507/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.847]
+Epoch 507/10001:  10%|█         | 1/10 [00:00<00:03,  2.42it/s, Loss=0.848]
+Epoch 507/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.848]
+Epoch 507/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.849]
+Epoch 507/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.847]
+Epoch 507/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.856]
+Epoch 507/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.852]
+Epoch 507/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.36it/s, Loss=0.852]
+Epoch 507/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.36it/s, Loss=0.848]
+Epoch 507/10001: 100%|██████████| 10/10 [00:00<00:00, 12.59it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 508/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 508/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 508/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.849]
+Epoch 508/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.852]
+Epoch 508/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.848]
+Epoch 508/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.845]
+Epoch 508/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.854]
+Epoch 508/10001:  50%|█████     | 5/10 [00:00<00:00, 10.58it/s, Loss=0.854]
+Epoch 508/10001:  50%|█████     | 5/10 [00:00<00:00, 10.58it/s, Loss=0.852]
+Epoch 508/10001:  50%|█████     | 5/10 [00:00<00:00, 10.58it/s, Loss=0.848]
+Epoch 508/10001:  50%|█████     | 5/10 [00:00<00:00, 10.58it/s, Loss=0.844]
+Epoch 508/10001:  50%|█████     | 5/10 [00:00<00:00, 10.58it/s, Loss=0.848]
+Epoch 508/10001:  50%|█████     | 5/10 [00:00<00:00, 10.58it/s, Loss=0.852]
+Epoch 508/10001: 100%|██████████| 10/10 [00:00<00:00, 12.69it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 509/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 509/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 509/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.85]
+Epoch 509/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.857]
+Epoch 509/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.849]
+Epoch 509/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.855]
+Epoch 509/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.849]
+Epoch 509/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.853]
+Epoch 509/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.852]
+Epoch 509/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.846]
+Epoch 509/10001:  80%|████████  | 8/10 [00:00<00:00, 20.74it/s, Loss=0.846]
+Epoch 509/10001:  80%|████████  | 8/10 [00:00<00:00, 20.74it/s, Loss=0.846]
+Epoch 509/10001:  80%|████████  | 8/10 [00:00<00:00, 20.74it/s, Loss=0.851]
+Epoch 509/10001: 100%|██████████| 10/10 [00:00<00:00, 15.71it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 510/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 510/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 510/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.854]
+Epoch 510/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.852]
+Epoch 510/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.853]
+Epoch 510/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.857]
+Epoch 510/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.85] 
+Epoch 510/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.85]
+Epoch 510/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.848]
+Epoch 510/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.851]
+Epoch 510/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.857]
+Epoch 510/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.849]
+Epoch 510/10001:  50%|█████     | 5/10 [00:00<00:00, 11.48it/s, Loss=0.846]
+Epoch 510/10001: 100%|██████████| 10/10 [00:00<00:00, 21.21it/s, Loss=0.846]
+Epoch 510/10001: 100%|██████████| 10/10 [00:00<00:00, 12.89it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 511/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 511/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 511/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.85]
+Epoch 511/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.85]
+Epoch 511/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.847]
+Epoch 511/10001:  10%|█         | 1/10 [00:00<00:04,  2.18it/s, Loss=0.849]
+Epoch 511/10001:  40%|████      | 4/10 [00:00<00:00,  8.55it/s, Loss=0.849]
+Epoch 511/10001:  40%|████      | 4/10 [00:00<00:00,  8.55it/s, Loss=0.851]
+Epoch 511/10001:  40%|████      | 4/10 [00:00<00:00,  8.55it/s, Loss=0.852]
+Epoch 511/10001:  40%|████      | 4/10 [00:00<00:00,  8.55it/s, Loss=0.856]
+Epoch 511/10001:  40%|████      | 4/10 [00:00<00:00,  8.55it/s, Loss=0.848]
+Epoch 511/10001:  80%|████████  | 8/10 [00:00<00:00, 15.94it/s, Loss=0.848]
+Epoch 511/10001:  80%|████████  | 8/10 [00:00<00:00, 15.94it/s, Loss=0.855]
+Epoch 511/10001:  80%|████████  | 8/10 [00:00<00:00, 15.94it/s, Loss=0.847]
+Epoch 511/10001: 100%|██████████| 10/10 [00:00<00:00, 11.42it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 512/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 512/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 512/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.848]
+Epoch 512/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.85] 
+Epoch 512/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.855]
+Epoch 512/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.844]
+Epoch 512/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.85] 
+Epoch 512/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.858]
+Epoch 512/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.858]
+Epoch 512/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.848]
+Epoch 512/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.858]
+Epoch 512/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.847]
+Epoch 512/10001:  60%|██████    | 6/10 [00:00<00:00, 13.80it/s, Loss=0.851]
+Epoch 512/10001: 100%|██████████| 10/10 [00:00<00:00, 13.72it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 513/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 513/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 513/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.849]
+Epoch 513/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.852]
+Epoch 513/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.848]
+Epoch 513/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.853]
+Epoch 513/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.848]
+Epoch 513/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.849]
+Epoch 513/10001:  60%|██████    | 6/10 [00:00<00:00, 15.27it/s, Loss=0.849]
+Epoch 513/10001:  60%|██████    | 6/10 [00:00<00:00, 15.27it/s, Loss=0.846]
+Epoch 513/10001:  60%|██████    | 6/10 [00:00<00:00, 15.27it/s, Loss=0.85] 
+Epoch 513/10001:  60%|██████    | 6/10 [00:00<00:00, 15.27it/s, Loss=0.856]
+Epoch 513/10001:  60%|██████    | 6/10 [00:00<00:00, 15.27it/s, Loss=0.85] 
+Epoch 513/10001: 100%|██████████| 10/10 [00:00<00:00, 15.23it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 514/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 514/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.856]
+Epoch 514/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.856]
+Epoch 514/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.854]
+Epoch 514/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.843]
+Epoch 514/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.855]
+Epoch 514/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.858]
+Epoch 514/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.849]
+Epoch 514/10001:  60%|██████    | 6/10 [00:00<00:00, 15.40it/s, Loss=0.849]
+Epoch 514/10001:  60%|██████    | 6/10 [00:00<00:00, 15.40it/s, Loss=0.852]
+Epoch 514/10001:  60%|██████    | 6/10 [00:00<00:00, 15.40it/s, Loss=0.852]
+Epoch 514/10001:  60%|██████    | 6/10 [00:00<00:00, 15.40it/s, Loss=0.844]
+Epoch 514/10001:  60%|██████    | 6/10 [00:00<00:00, 15.40it/s, Loss=0.85] 
+Epoch 514/10001: 100%|██████████| 10/10 [00:00<00:00, 15.22it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 515/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 515/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 515/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.849]
+Epoch 515/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.849]
+Epoch 515/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.851]
+Epoch 515/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.854]
+Epoch 515/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.852]
+Epoch 515/10001:  50%|█████     | 5/10 [00:00<00:00, 12.20it/s, Loss=0.852]
+Epoch 515/10001:  50%|█████     | 5/10 [00:00<00:00, 12.20it/s, Loss=0.854]
+Epoch 515/10001:  50%|█████     | 5/10 [00:00<00:00, 12.20it/s, Loss=0.855]
+Epoch 515/10001:  50%|█████     | 5/10 [00:00<00:00, 12.20it/s, Loss=0.85] 
+Epoch 515/10001:  50%|█████     | 5/10 [00:00<00:00, 12.20it/s, Loss=0.851]
+Epoch 515/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.05it/s, Loss=0.851]
+Epoch 515/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.05it/s, Loss=0.85] 
+Epoch 515/10001: 100%|██████████| 10/10 [00:00<00:00, 13.38it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 516/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 516/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 516/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.853]
+Epoch 516/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.846]
+Epoch 516/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.847]
+Epoch 516/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.849]
+Epoch 516/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.855]
+Epoch 516/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.856]
+Epoch 516/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.852]
+Epoch 516/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.856]
+Epoch 516/10001:  80%|████████  | 8/10 [00:00<00:00, 21.08it/s, Loss=0.856]
+Epoch 516/10001:  80%|████████  | 8/10 [00:00<00:00, 21.08it/s, Loss=0.853]
+Epoch 516/10001:  80%|████████  | 8/10 [00:00<00:00, 21.08it/s, Loss=0.852]
+Epoch 516/10001: 100%|██████████| 10/10 [00:00<00:00, 15.98it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 517/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 517/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 517/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.851]
+Epoch 517/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.854]
+Epoch 517/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.854]
+Epoch 517/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.848]
+Epoch 517/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.86] 
+Epoch 517/10001:  50%|█████     | 5/10 [00:00<00:00, 10.65it/s, Loss=0.86]
+Epoch 517/10001:  50%|█████     | 5/10 [00:00<00:00, 10.65it/s, Loss=0.849]
+Epoch 517/10001:  50%|█████     | 5/10 [00:00<00:00, 10.65it/s, Loss=0.853]
+Epoch 517/10001:  50%|█████     | 5/10 [00:00<00:00, 10.65it/s, Loss=0.85] 
+Epoch 517/10001:  50%|█████     | 5/10 [00:00<00:00, 10.65it/s, Loss=0.856]
+Epoch 517/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.43it/s, Loss=0.856]
+Epoch 517/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.43it/s, Loss=0.854]
+Epoch 517/10001: 100%|██████████| 10/10 [00:00<00:00, 11.95it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 518/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 518/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 518/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.851]
+Epoch 518/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.849]
+Epoch 518/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.847]
+Epoch 518/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.856]
+Epoch 518/10001:  10%|█         | 1/10 [00:00<00:04,  2.12it/s, Loss=0.845]
+Epoch 518/10001:  50%|█████     | 5/10 [00:00<00:00, 10.57it/s, Loss=0.845]
+Epoch 518/10001:  50%|█████     | 5/10 [00:00<00:00, 10.57it/s, Loss=0.849]
+Epoch 518/10001:  50%|█████     | 5/10 [00:00<00:00, 10.57it/s, Loss=0.862]
+Epoch 518/10001:  50%|█████     | 5/10 [00:00<00:00, 10.57it/s, Loss=0.854]
+Epoch 518/10001:  50%|█████     | 5/10 [00:00<00:00, 10.57it/s, Loss=0.852]
+Epoch 518/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.29it/s, Loss=0.852]
+Epoch 518/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.29it/s, Loss=0.853]
+Epoch 518/10001: 100%|██████████| 10/10 [00:00<00:00, 11.78it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 519/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 519/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 519/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.853]
+Epoch 519/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.852]
+Epoch 519/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.849]
+Epoch 519/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.849]
+Epoch 519/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.849]
+Epoch 519/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.848]
+Epoch 519/10001:  60%|██████    | 6/10 [00:00<00:00, 13.61it/s, Loss=0.848]
+Epoch 519/10001:  60%|██████    | 6/10 [00:00<00:00, 13.61it/s, Loss=0.852]
+Epoch 519/10001:  60%|██████    | 6/10 [00:00<00:00, 13.61it/s, Loss=0.853]
+Epoch 519/10001:  60%|██████    | 6/10 [00:00<00:00, 13.61it/s, Loss=0.851]
+Epoch 519/10001:  60%|██████    | 6/10 [00:00<00:00, 13.61it/s, Loss=0.851]
+Epoch 519/10001: 100%|██████████| 10/10 [00:00<00:00, 13.68it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 520/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 520/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 520/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.846]
+Epoch 520/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.853]
+Epoch 520/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.855]
+Epoch 520/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.855]
+Epoch 520/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.85] 
+Epoch 520/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.854]
+Epoch 520/10001:  60%|██████    | 6/10 [00:00<00:00, 15.37it/s, Loss=0.854]
+Epoch 520/10001:  60%|██████    | 6/10 [00:00<00:00, 15.37it/s, Loss=0.842]
+Epoch 520/10001:  60%|██████    | 6/10 [00:00<00:00, 15.37it/s, Loss=0.855]
+Epoch 520/10001:  60%|██████    | 6/10 [00:00<00:00, 15.37it/s, Loss=0.855]
+Epoch 520/10001:  60%|██████    | 6/10 [00:00<00:00, 15.37it/s, Loss=0.851]
+Epoch 520/10001: 100%|██████████| 10/10 [00:00<00:00, 14.91it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 521/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 521/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 521/10001:  10%|█         | 1/10 [00:00<00:05,  1.62it/s, Loss=0.858]
+Epoch 521/10001:  10%|█         | 1/10 [00:00<00:05,  1.62it/s, Loss=0.857]
+Epoch 521/10001:  10%|█         | 1/10 [00:00<00:05,  1.62it/s, Loss=0.856]
+Epoch 521/10001:  10%|█         | 1/10 [00:00<00:05,  1.62it/s, Loss=0.846]
+Epoch 521/10001:  10%|█         | 1/10 [00:00<00:05,  1.62it/s, Loss=0.857]
+Epoch 521/10001:  10%|█         | 1/10 [00:00<00:05,  1.62it/s, Loss=0.852]
+Epoch 521/10001:  60%|██████    | 6/10 [00:00<00:00, 10.59it/s, Loss=0.852]
+Epoch 521/10001:  60%|██████    | 6/10 [00:00<00:00, 10.59it/s, Loss=0.854]
+Epoch 521/10001:  60%|██████    | 6/10 [00:00<00:00, 10.59it/s, Loss=0.851]
+Epoch 521/10001:  60%|██████    | 6/10 [00:00<00:00, 10.59it/s, Loss=0.86] 
+Epoch 521/10001:  60%|██████    | 6/10 [00:00<00:00, 10.59it/s, Loss=0.851]
+Epoch 521/10001: 100%|██████████| 10/10 [00:00<00:00, 10.93it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 522/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 522/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 522/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.849]
+Epoch 522/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.845]
+Epoch 522/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.848]
+Epoch 522/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.849]
+Epoch 522/10001:  40%|████      | 4/10 [00:00<00:00, 10.15it/s, Loss=0.849]
+Epoch 522/10001:  40%|████      | 4/10 [00:00<00:00, 10.15it/s, Loss=0.854]
+Epoch 522/10001:  40%|████      | 4/10 [00:00<00:00, 10.15it/s, Loss=0.845]
+Epoch 522/10001:  40%|████      | 4/10 [00:00<00:00, 10.15it/s, Loss=0.847]
+Epoch 522/10001:  40%|████      | 4/10 [00:00<00:00, 10.15it/s, Loss=0.854]
+Epoch 522/10001:  40%|████      | 4/10 [00:00<00:00, 10.15it/s, Loss=0.849]
+Epoch 522/10001:  90%|█████████ | 9/10 [00:00<00:00, 21.34it/s, Loss=0.849]
+Epoch 522/10001:  90%|█████████ | 9/10 [00:00<00:00, 21.34it/s, Loss=0.857]
+Epoch 522/10001: 100%|██████████| 10/10 [00:00<00:00, 14.04it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 523/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 523/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 523/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.848]
+Epoch 523/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.846]
+Epoch 523/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.859]
+Epoch 523/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.845]
+Epoch 523/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.856]
+Epoch 523/10001:  10%|█         | 1/10 [00:00<00:03,  2.29it/s, Loss=0.855]
+Epoch 523/10001:  60%|██████    | 6/10 [00:00<00:00, 13.72it/s, Loss=0.855]
+Epoch 523/10001:  60%|██████    | 6/10 [00:00<00:00, 13.72it/s, Loss=0.852]
+Epoch 523/10001:  60%|██████    | 6/10 [00:00<00:00, 13.72it/s, Loss=0.86] 
+Epoch 523/10001:  60%|██████    | 6/10 [00:00<00:00, 13.72it/s, Loss=0.855]
+Epoch 523/10001:  60%|██████    | 6/10 [00:00<00:00, 13.72it/s, Loss=0.854]
+Epoch 523/10001: 100%|██████████| 10/10 [00:00<00:00, 13.71it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 524/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 524/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 524/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.851]
+Epoch 524/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.847]
+Epoch 524/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.847]
+Epoch 524/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.845]
+Epoch 524/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.856]
+Epoch 524/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.856]
+Epoch 524/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.847]
+Epoch 524/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.855]
+Epoch 524/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.853]
+Epoch 524/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.842]
+Epoch 524/10001:  50%|█████     | 5/10 [00:00<00:00, 11.85it/s, Loss=0.853]
+Epoch 524/10001: 100%|██████████| 10/10 [00:00<00:00, 13.75it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 525/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 525/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 525/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.855]
+Epoch 525/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.854]
+Epoch 525/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.846]
+Epoch 525/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.847]
+Epoch 525/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.85] 
+Epoch 525/10001:  10%|█         | 1/10 [00:00<00:04,  2.19it/s, Loss=0.851]
+Epoch 525/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.851]
+Epoch 525/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.849]
+Epoch 525/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.846]
+Epoch 525/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.844]
+Epoch 525/10001:  60%|██████    | 6/10 [00:00<00:00, 13.35it/s, Loss=0.849]
+Epoch 525/10001: 100%|██████████| 10/10 [00:00<00:00, 13.21it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 526/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 526/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 526/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.853]
+Epoch 526/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.85] 
+Epoch 526/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.845]
+Epoch 526/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.846]
+Epoch 526/10001:  40%|████      | 4/10 [00:00<00:00,  9.53it/s, Loss=0.846]
+Epoch 526/10001:  40%|████      | 4/10 [00:00<00:00,  9.53it/s, Loss=0.854]
+Epoch 526/10001:  40%|████      | 4/10 [00:00<00:00,  9.53it/s, Loss=0.848]
+Epoch 526/10001:  40%|████      | 4/10 [00:00<00:00,  9.53it/s, Loss=0.843]
+Epoch 526/10001:  40%|████      | 4/10 [00:00<00:00,  9.53it/s, Loss=0.851]
+Epoch 526/10001:  40%|████      | 4/10 [00:00<00:00,  9.53it/s, Loss=0.858]
+Epoch 526/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.56it/s, Loss=0.858]
+Epoch 526/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.56it/s, Loss=0.855]
+Epoch 526/10001: 100%|██████████| 10/10 [00:00<00:00, 13.20it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 527/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 527/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 527/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.848]
+Epoch 527/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.851]
+Epoch 527/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.841]
+Epoch 527/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.859]
+Epoch 527/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.849]
+Epoch 527/10001:  10%|█         | 1/10 [00:00<00:03,  2.69it/s, Loss=0.846]
+Epoch 527/10001:  60%|██████    | 6/10 [00:00<00:00, 15.04it/s, Loss=0.846]
+Epoch 527/10001:  60%|██████    | 6/10 [00:00<00:00, 15.04it/s, Loss=0.842]
+Epoch 527/10001:  60%|██████    | 6/10 [00:00<00:00, 15.04it/s, Loss=0.848]
+Epoch 527/10001:  60%|██████    | 6/10 [00:00<00:00, 15.04it/s, Loss=0.851]
+Epoch 527/10001:  60%|██████    | 6/10 [00:00<00:00, 15.04it/s, Loss=0.849]
+Epoch 527/10001: 100%|██████████| 10/10 [00:00<00:00, 20.54it/s, Loss=0.849]
+Epoch 527/10001: 100%|██████████| 10/10 [00:00<00:00, 13.53it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 528/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 528/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 528/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.848]
+Epoch 528/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.852]
+Epoch 528/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.849]
+Epoch 528/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.854]
+Epoch 528/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.844]
+Epoch 528/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.844]
+Epoch 528/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.846]
+Epoch 528/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.851]
+Epoch 528/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.846]
+Epoch 528/10001:  50%|█████     | 5/10 [00:00<00:00, 10.93it/s, Loss=0.856]
+Epoch 528/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.55it/s, Loss=0.856]
+Epoch 528/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.55it/s, Loss=0.848]
+Epoch 528/10001: 100%|██████████| 10/10 [00:00<00:00, 12.30it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 529/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 529/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 529/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.858]
+Epoch 529/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.845]
+Epoch 529/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.861]
+Epoch 529/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.852]
+Epoch 529/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.856]
+Epoch 529/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.856]
+Epoch 529/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.858]
+Epoch 529/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.847]
+Epoch 529/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.857]
+Epoch 529/10001:  50%|█████     | 5/10 [00:00<00:00, 12.22it/s, Loss=0.848]
+Epoch 529/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.95it/s, Loss=0.848]
+Epoch 529/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.95it/s, Loss=0.851]
+Epoch 529/10001: 100%|██████████| 10/10 [00:00<00:00, 13.31it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 530/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 530/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 530/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.846]
+Epoch 530/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.851]
+Epoch 530/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.849]
+Epoch 530/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.85] 
+Epoch 530/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.857]
+Epoch 530/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.855]
+Epoch 530/10001:  10%|█         | 1/10 [00:00<00:03,  2.66it/s, Loss=0.846]
+Epoch 530/10001:  70%|███████   | 7/10 [00:00<00:00, 18.10it/s, Loss=0.846]
+Epoch 530/10001:  70%|███████   | 7/10 [00:00<00:00, 18.10it/s, Loss=0.853]
+Epoch 530/10001:  70%|███████   | 7/10 [00:00<00:00, 18.10it/s, Loss=0.849]
+Epoch 530/10001:  70%|███████   | 7/10 [00:00<00:00, 18.10it/s, Loss=0.854]
+Epoch 530/10001: 100%|██████████| 10/10 [00:00<00:00, 15.76it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 531/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 531/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 531/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.852]
+Epoch 531/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.838]
+Epoch 531/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.854]
+Epoch 531/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.845]
+Epoch 531/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.852]
+Epoch 531/10001:  10%|█         | 1/10 [00:00<00:03,  2.77it/s, Loss=0.842]
+Epoch 531/10001:  60%|██████    | 6/10 [00:00<00:00, 15.67it/s, Loss=0.842]
+Epoch 531/10001:  60%|██████    | 6/10 [00:00<00:00, 15.67it/s, Loss=0.85] 
+Epoch 531/10001:  60%|██████    | 6/10 [00:00<00:00, 15.67it/s, Loss=0.851]
+Epoch 531/10001:  60%|██████    | 6/10 [00:00<00:00, 15.67it/s, Loss=0.855]
+Epoch 531/10001:  60%|██████    | 6/10 [00:00<00:00, 15.67it/s, Loss=0.862]
+Epoch 531/10001: 100%|██████████| 10/10 [00:00<00:00, 15.34it/s, Loss=0.862]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 532/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 532/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 532/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.847]
+Epoch 532/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.851]
+Epoch 532/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.851]
+Epoch 532/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.851]
+Epoch 532/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.85] 
+Epoch 532/10001:  10%|█         | 1/10 [00:00<00:03,  2.38it/s, Loss=0.851]
+Epoch 532/10001:  60%|██████    | 6/10 [00:00<00:00, 14.09it/s, Loss=0.851]
+Epoch 532/10001:  60%|██████    | 6/10 [00:00<00:00, 14.09it/s, Loss=0.858]
+Epoch 532/10001:  60%|██████    | 6/10 [00:00<00:00, 14.09it/s, Loss=0.844]
+Epoch 532/10001:  60%|██████    | 6/10 [00:00<00:00, 14.09it/s, Loss=0.846]
+Epoch 532/10001:  60%|██████    | 6/10 [00:00<00:00, 14.09it/s, Loss=0.857]
+Epoch 532/10001: 100%|██████████| 10/10 [00:00<00:00, 20.52it/s, Loss=0.857]
+Epoch 532/10001: 100%|██████████| 10/10 [00:00<00:00, 13.15it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 533/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 533/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 533/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.854]
+Epoch 533/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.856]
+Epoch 533/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.851]
+Epoch 533/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.845]
+Epoch 533/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.857]
+Epoch 533/10001:  10%|█         | 1/10 [00:00<00:03,  2.87it/s, Loss=0.858]
+Epoch 533/10001:  60%|██████    | 6/10 [00:00<00:00, 15.64it/s, Loss=0.858]
+Epoch 533/10001:  60%|██████    | 6/10 [00:00<00:00, 15.64it/s, Loss=0.855]
+Epoch 533/10001:  60%|██████    | 6/10 [00:00<00:00, 15.64it/s, Loss=0.847]
+Epoch 533/10001:  60%|██████    | 6/10 [00:00<00:00, 15.64it/s, Loss=0.842]
+Epoch 533/10001:  60%|██████    | 6/10 [00:00<00:00, 15.64it/s, Loss=0.859]
+Epoch 533/10001: 100%|██████████| 10/10 [00:00<00:00, 15.15it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 534/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 534/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 534/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.847]
+Epoch 534/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.852]
+Epoch 534/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.852]
+Epoch 534/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.852]
+Epoch 534/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.855]
+Epoch 534/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.855]
+Epoch 534/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.853]
+Epoch 534/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.845]
+Epoch 534/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.85] 
+Epoch 534/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.852]
+Epoch 534/10001:  50%|█████     | 5/10 [00:00<00:00, 11.54it/s, Loss=0.852]
+Epoch 534/10001: 100%|██████████| 10/10 [00:00<00:00, 20.90it/s, Loss=0.852]
+Epoch 534/10001: 100%|██████████| 10/10 [00:00<00:00, 13.31it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 535/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 535/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 535/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.847]
+Epoch 535/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.848]
+Epoch 535/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.85] 
+Epoch 535/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.855]
+Epoch 535/10001:  40%|████      | 4/10 [00:00<00:00,  9.06it/s, Loss=0.855]
+Epoch 535/10001:  40%|████      | 4/10 [00:00<00:00,  9.06it/s, Loss=0.848]
+Epoch 535/10001:  40%|████      | 4/10 [00:00<00:00,  9.06it/s, Loss=0.847]
+Epoch 535/10001:  40%|████      | 4/10 [00:00<00:00,  9.06it/s, Loss=0.845]
+Epoch 535/10001:  40%|████      | 4/10 [00:00<00:00,  9.06it/s, Loss=0.855]
+Epoch 535/10001:  80%|████████  | 8/10 [00:00<00:00, 16.46it/s, Loss=0.855]
+Epoch 535/10001:  80%|████████  | 8/10 [00:00<00:00, 16.46it/s, Loss=0.859]
+Epoch 535/10001:  80%|████████  | 8/10 [00:00<00:00, 16.46it/s, Loss=0.855]
+Epoch 535/10001: 100%|██████████| 10/10 [00:00<00:00, 12.49it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 536/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 536/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 536/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.857]
+Epoch 536/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.855]
+Epoch 536/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.852]
+Epoch 536/10001:  10%|█         | 1/10 [00:00<00:03,  2.78it/s, Loss=0.851]
+Epoch 536/10001:  40%|████      | 4/10 [00:00<00:00, 10.39it/s, Loss=0.851]
+Epoch 536/10001:  40%|████      | 4/10 [00:00<00:00, 10.39it/s, Loss=0.847]
+Epoch 536/10001:  40%|████      | 4/10 [00:00<00:00, 10.39it/s, Loss=0.854]
+Epoch 536/10001:  40%|████      | 4/10 [00:00<00:00, 10.39it/s, Loss=0.849]
+Epoch 536/10001:  40%|████      | 4/10 [00:00<00:00, 10.39it/s, Loss=0.857]
+Epoch 536/10001:  80%|████████  | 8/10 [00:00<00:00, 18.29it/s, Loss=0.857]
+Epoch 536/10001:  80%|████████  | 8/10 [00:00<00:00, 18.29it/s, Loss=0.855]
+Epoch 536/10001:  80%|████████  | 8/10 [00:00<00:00, 18.29it/s, Loss=0.854]
+Epoch 536/10001: 100%|██████████| 10/10 [00:00<00:00, 13.77it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 537/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 537/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 537/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.845]
+Epoch 537/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.842]
+Epoch 537/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.848]
+Epoch 537/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.851]
+Epoch 537/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.855]
+Epoch 537/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.839]
+Epoch 537/10001:  60%|██████    | 6/10 [00:00<00:00, 13.39it/s, Loss=0.839]
+Epoch 537/10001:  60%|██████    | 6/10 [00:00<00:00, 13.39it/s, Loss=0.855]
+Epoch 537/10001:  60%|██████    | 6/10 [00:00<00:00, 13.39it/s, Loss=0.856]
+Epoch 537/10001:  60%|██████    | 6/10 [00:00<00:00, 13.39it/s, Loss=0.854]
+Epoch 537/10001:  60%|██████    | 6/10 [00:00<00:00, 13.39it/s, Loss=0.852]
+Epoch 537/10001: 100%|██████████| 10/10 [00:00<00:00, 12.18it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 538/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 538/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 538/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.853]
+Epoch 538/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.853]
+Epoch 538/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.852]
+Epoch 538/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.856]
+Epoch 538/10001:  40%|████      | 4/10 [00:00<00:00,  9.16it/s, Loss=0.856]
+Epoch 538/10001:  40%|████      | 4/10 [00:00<00:00,  9.16it/s, Loss=0.848]
+Epoch 538/10001:  40%|████      | 4/10 [00:00<00:00,  9.16it/s, Loss=0.848]
+Epoch 538/10001:  40%|████      | 4/10 [00:00<00:00,  9.16it/s, Loss=0.851]
+Epoch 538/10001:  40%|████      | 4/10 [00:00<00:00,  9.16it/s, Loss=0.859]
+Epoch 538/10001:  40%|████      | 4/10 [00:00<00:00,  9.16it/s, Loss=0.852]
+Epoch 538/10001:  40%|████      | 4/10 [00:00<00:00,  9.16it/s, Loss=0.847]
+Epoch 538/10001: 100%|██████████| 10/10 [00:00<00:00, 21.26it/s, Loss=0.847]
+Epoch 538/10001: 100%|██████████| 10/10 [00:00<00:00, 13.12it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 539/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 539/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.842]
+Epoch 539/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.842]
+Epoch 539/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.844]
+Epoch 539/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.844]
+Epoch 539/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.852]
+Epoch 539/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.847]
+Epoch 539/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.847]
+Epoch 539/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.854]
+Epoch 539/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.857]
+Epoch 539/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.855]
+Epoch 539/10001:  50%|█████     | 5/10 [00:00<00:00, 11.01it/s, Loss=0.856]
+Epoch 539/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.10it/s, Loss=0.856]
+Epoch 539/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.10it/s, Loss=0.846]
+Epoch 539/10001: 100%|██████████| 10/10 [00:00<00:00, 12.57it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 540/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 540/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 540/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.854]
+Epoch 540/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.85] 
+Epoch 540/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.851]
+Epoch 540/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.859]
+Epoch 540/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.85] 
+Epoch 540/10001:  10%|█         | 1/10 [00:00<00:04,  2.07it/s, Loss=0.849]
+Epoch 540/10001:  60%|██████    | 6/10 [00:00<00:00, 12.79it/s, Loss=0.849]
+Epoch 540/10001:  60%|██████    | 6/10 [00:00<00:00, 12.79it/s, Loss=0.851]
+Epoch 540/10001:  60%|██████    | 6/10 [00:00<00:00, 12.79it/s, Loss=0.846]
+Epoch 540/10001:  60%|██████    | 6/10 [00:00<00:00, 12.79it/s, Loss=0.844]
+Epoch 540/10001:  60%|██████    | 6/10 [00:00<00:00, 12.79it/s, Loss=0.855]
+Epoch 540/10001: 100%|██████████| 10/10 [00:00<00:00, 12.87it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 541/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 541/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 541/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.849]
+Epoch 541/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.843]
+Epoch 541/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.854]
+Epoch 541/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.845]
+Epoch 541/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.853]
+Epoch 541/10001:  10%|█         | 1/10 [00:00<00:03,  2.79it/s, Loss=0.854]
+Epoch 541/10001:  60%|██████    | 6/10 [00:00<00:00, 16.01it/s, Loss=0.854]
+Epoch 541/10001:  60%|██████    | 6/10 [00:00<00:00, 16.01it/s, Loss=0.854]
+Epoch 541/10001:  60%|██████    | 6/10 [00:00<00:00, 16.01it/s, Loss=0.85] 
+Epoch 541/10001:  60%|██████    | 6/10 [00:00<00:00, 16.01it/s, Loss=0.84]
+Epoch 541/10001:  60%|██████    | 6/10 [00:00<00:00, 16.01it/s, Loss=0.856]
+Epoch 541/10001: 100%|██████████| 10/10 [00:00<00:00, 15.32it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 542/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 542/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 542/10001:  10%|█         | 1/10 [00:00<00:04,  1.83it/s, Loss=0.847]
+Epoch 542/10001:  10%|█         | 1/10 [00:00<00:04,  1.83it/s, Loss=0.848]
+Epoch 542/10001:  10%|█         | 1/10 [00:00<00:04,  1.83it/s, Loss=0.847]
+Epoch 542/10001:  10%|█         | 1/10 [00:00<00:04,  1.83it/s, Loss=0.848]
+Epoch 542/10001:  10%|█         | 1/10 [00:00<00:04,  1.83it/s, Loss=0.858]
+Epoch 542/10001:  10%|█         | 1/10 [00:00<00:04,  1.83it/s, Loss=0.857]
+Epoch 542/10001:  10%|█         | 1/10 [00:00<00:04,  1.83it/s, Loss=0.858]
+Epoch 542/10001:  10%|█         | 1/10 [00:00<00:04,  1.83it/s, Loss=0.851]
+Epoch 542/10001:  10%|█         | 1/10 [00:00<00:04,  1.83it/s, Loss=0.847]
+Epoch 542/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.64it/s, Loss=0.847]
+Epoch 542/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.64it/s, Loss=0.851]
+Epoch 542/10001: 100%|██████████| 10/10 [00:00<00:00, 12.79it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 543/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 543/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 543/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.85]
+Epoch 543/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.854]
+Epoch 543/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.854]
+Epoch 543/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.856]
+Epoch 543/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.846]
+Epoch 543/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.854]
+Epoch 543/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.854]
+Epoch 543/10001:  70%|███████   | 7/10 [00:00<00:00, 15.32it/s, Loss=0.854]
+Epoch 543/10001:  70%|███████   | 7/10 [00:00<00:00, 15.32it/s, Loss=0.852]
+Epoch 543/10001:  70%|███████   | 7/10 [00:00<00:00, 15.32it/s, Loss=0.851]
+Epoch 543/10001:  70%|███████   | 7/10 [00:00<00:00, 15.32it/s, Loss=0.851]
+Epoch 543/10001: 100%|██████████| 10/10 [00:00<00:00, 13.00it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 544/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 544/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.858]
+Epoch 544/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.858]
+Epoch 544/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.853]
+Epoch 544/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.85] 
+Epoch 544/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.848]
+Epoch 544/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.853]
+Epoch 544/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.85] 
+Epoch 544/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.85]
+Epoch 544/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.853]
+Epoch 544/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.844]
+Epoch 544/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.849]
+Epoch 544/10001:  60%|██████    | 6/10 [00:00<00:00, 13.12it/s, Loss=0.845]
+Epoch 544/10001: 100%|██████████| 10/10 [00:00<00:00, 13.39it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 545/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 545/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 545/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.849]
+Epoch 545/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.85] 
+Epoch 545/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.856]
+Epoch 545/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.847]
+Epoch 545/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.85] 
+Epoch 545/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.855]
+Epoch 545/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.845]
+Epoch 545/10001:  70%|███████   | 7/10 [00:00<00:00, 16.11it/s, Loss=0.845]
+Epoch 545/10001:  70%|███████   | 7/10 [00:00<00:00, 16.11it/s, Loss=0.847]
+Epoch 545/10001:  70%|███████   | 7/10 [00:00<00:00, 16.11it/s, Loss=0.851]
+Epoch 545/10001:  70%|███████   | 7/10 [00:00<00:00, 16.11it/s, Loss=0.849]
+Epoch 545/10001: 100%|██████████| 10/10 [00:00<00:00, 14.18it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 546/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 546/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 546/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.855]
+Epoch 546/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.865]
+Epoch 546/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.848]
+Epoch 546/10001:  10%|█         | 1/10 [00:00<00:03,  2.46it/s, Loss=0.851]
+Epoch 546/10001:  40%|████      | 4/10 [00:00<00:00,  9.47it/s, Loss=0.851]
+Epoch 546/10001:  40%|████      | 4/10 [00:00<00:00,  9.47it/s, Loss=0.855]
+Epoch 546/10001:  40%|████      | 4/10 [00:00<00:00,  9.47it/s, Loss=0.85] 
+Epoch 546/10001:  40%|████      | 4/10 [00:00<00:00,  9.47it/s, Loss=0.853]
+Epoch 546/10001:  40%|████      | 4/10 [00:00<00:00,  9.47it/s, Loss=0.848]
+Epoch 546/10001:  80%|████████  | 8/10 [00:00<00:00, 17.14it/s, Loss=0.848]
+Epoch 546/10001:  80%|████████  | 8/10 [00:00<00:00, 17.14it/s, Loss=0.853]
+Epoch 546/10001:  80%|████████  | 8/10 [00:00<00:00, 17.14it/s, Loss=0.854]
+Epoch 546/10001: 100%|██████████| 10/10 [00:00<00:00, 12.47it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 547/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 547/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 547/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.843]
+Epoch 547/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.857]
+Epoch 547/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.847]
+Epoch 547/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.851]
+Epoch 547/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.855]
+Epoch 547/10001:  10%|█         | 1/10 [00:00<00:04,  2.06it/s, Loss=0.852]
+Epoch 547/10001:  60%|██████    | 6/10 [00:00<00:00, 12.84it/s, Loss=0.852]
+Epoch 547/10001:  60%|██████    | 6/10 [00:00<00:00, 12.84it/s, Loss=0.856]
+Epoch 547/10001:  60%|██████    | 6/10 [00:00<00:00, 12.84it/s, Loss=0.856]
+Epoch 547/10001:  60%|██████    | 6/10 [00:00<00:00, 12.84it/s, Loss=0.85] 
+Epoch 547/10001:  60%|██████    | 6/10 [00:00<00:00, 12.84it/s, Loss=0.852]
+Epoch 547/10001: 100%|██████████| 10/10 [00:00<00:00, 12.82it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 548/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 548/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 548/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.849]
+Epoch 548/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.847]
+Epoch 548/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.846]
+Epoch 548/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.849]
+Epoch 548/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.851]
+Epoch 548/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.856]
+Epoch 548/10001:  60%|██████    | 6/10 [00:00<00:00, 15.59it/s, Loss=0.856]
+Epoch 548/10001:  60%|██████    | 6/10 [00:00<00:00, 15.59it/s, Loss=0.857]
+Epoch 548/10001:  60%|██████    | 6/10 [00:00<00:00, 15.59it/s, Loss=0.852]
+Epoch 548/10001:  60%|██████    | 6/10 [00:00<00:00, 15.59it/s, Loss=0.848]
+Epoch 548/10001:  60%|██████    | 6/10 [00:00<00:00, 15.59it/s, Loss=0.848]
+Epoch 548/10001: 100%|██████████| 10/10 [00:00<00:00, 14.70it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 549/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 549/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 549/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.857]
+Epoch 549/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.855]
+Epoch 549/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.848]
+Epoch 549/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.85] 
+Epoch 549/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.848]
+Epoch 549/10001:  50%|█████     | 5/10 [00:00<00:00, 11.38it/s, Loss=0.848]
+Epoch 549/10001:  50%|█████     | 5/10 [00:00<00:00, 11.38it/s, Loss=0.843]
+Epoch 549/10001:  50%|█████     | 5/10 [00:00<00:00, 11.38it/s, Loss=0.854]
+Epoch 549/10001:  50%|█████     | 5/10 [00:00<00:00, 11.38it/s, Loss=0.85] 
+Epoch 549/10001:  50%|█████     | 5/10 [00:00<00:00, 11.38it/s, Loss=0.858]
+Epoch 549/10001:  50%|█████     | 5/10 [00:00<00:00, 11.38it/s, Loss=0.845]
+Epoch 549/10001: 100%|██████████| 10/10 [00:00<00:00, 13.16it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 550/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 550/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 550/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.853]
+Epoch 550/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.857]
+Epoch 550/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.86] 
+Epoch 550/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.855]
+Epoch 550/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.854]
+Epoch 550/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.847]
+Epoch 550/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.847]
+Epoch 550/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.85] 
+Epoch 550/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.852]
+Epoch 550/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.852]
+Epoch 550/10001:  60%|██████    | 6/10 [00:00<00:00, 13.29it/s, Loss=0.855]
+Epoch 550/10001: 100%|██████████| 10/10 [00:00<00:00, 13.28it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 551/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 551/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 551/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.855]
+Epoch 551/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.849]
+Epoch 551/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.849]
+Epoch 551/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.859]
+Epoch 551/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.855]
+Epoch 551/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.847]
+Epoch 551/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.851]
+Epoch 551/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.843]
+Epoch 551/10001:  80%|████████  | 8/10 [00:00<00:00, 21.60it/s, Loss=0.843]
+Epoch 551/10001:  80%|████████  | 8/10 [00:00<00:00, 21.60it/s, Loss=0.857]
+Epoch 551/10001:  80%|████████  | 8/10 [00:00<00:00, 21.60it/s, Loss=0.85] 
+Epoch 551/10001: 100%|██████████| 10/10 [00:00<00:00, 16.80it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 552/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 552/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 552/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.846]
+Epoch 552/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.844]
+Epoch 552/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.861]
+Epoch 552/10001:  10%|█         | 1/10 [00:00<00:03,  2.64it/s, Loss=0.849]
+Epoch 552/10001:  40%|████      | 4/10 [00:00<00:00, 10.08it/s, Loss=0.849]
+Epoch 552/10001:  40%|████      | 4/10 [00:00<00:00, 10.08it/s, Loss=0.856]
+Epoch 552/10001:  40%|████      | 4/10 [00:00<00:00, 10.08it/s, Loss=0.849]
+Epoch 552/10001:  40%|████      | 4/10 [00:00<00:00, 10.08it/s, Loss=0.856]
+Epoch 552/10001:  40%|████      | 4/10 [00:00<00:00, 10.08it/s, Loss=0.844]
+Epoch 552/10001:  80%|████████  | 8/10 [00:00<00:00, 17.81it/s, Loss=0.844]
+Epoch 552/10001:  80%|████████  | 8/10 [00:00<00:00, 17.81it/s, Loss=0.852]
+Epoch 552/10001:  80%|████████  | 8/10 [00:00<00:00, 17.81it/s, Loss=0.841]
+Epoch 552/10001: 100%|██████████| 10/10 [00:00<00:00, 12.62it/s, Loss=0.841]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 553/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 553/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 553/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.849]
+Epoch 553/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.854]
+Epoch 553/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.857]
+Epoch 553/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.849]
+Epoch 553/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.854]
+Epoch 553/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.855]
+Epoch 553/10001:  60%|██████    | 6/10 [00:00<00:00, 14.28it/s, Loss=0.855]
+Epoch 553/10001:  60%|██████    | 6/10 [00:00<00:00, 14.28it/s, Loss=0.86] 
+Epoch 553/10001:  60%|██████    | 6/10 [00:00<00:00, 14.28it/s, Loss=0.851]
+Epoch 553/10001:  60%|██████    | 6/10 [00:00<00:00, 14.28it/s, Loss=0.842]
+Epoch 553/10001:  60%|██████    | 6/10 [00:00<00:00, 14.28it/s, Loss=0.85] 
+Epoch 553/10001: 100%|██████████| 10/10 [00:00<00:00, 13.51it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 554/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 554/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 554/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.851]
+Epoch 554/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.851]
+Epoch 554/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.852]
+Epoch 554/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.848]
+Epoch 554/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.858]
+Epoch 554/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.849]
+Epoch 554/10001:  60%|██████    | 6/10 [00:00<00:00, 13.91it/s, Loss=0.849]
+Epoch 554/10001:  60%|██████    | 6/10 [00:00<00:00, 13.91it/s, Loss=0.849]
+Epoch 554/10001:  60%|██████    | 6/10 [00:00<00:00, 13.91it/s, Loss=0.854]
+Epoch 554/10001:  60%|██████    | 6/10 [00:00<00:00, 13.91it/s, Loss=0.86] 
+Epoch 554/10001:  60%|██████    | 6/10 [00:00<00:00, 13.91it/s, Loss=0.851]
+Epoch 554/10001: 100%|██████████| 10/10 [00:00<00:00, 13.79it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 555/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 555/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 555/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.849]
+Epoch 555/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.853]
+Epoch 555/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.851]
+Epoch 555/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.855]
+Epoch 555/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.849]
+Epoch 555/10001:  10%|█         | 1/10 [00:00<00:03,  2.68it/s, Loss=0.855]
+Epoch 555/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.855]
+Epoch 555/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.857]
+Epoch 555/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.859]
+Epoch 555/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.851]
+Epoch 555/10001:  60%|██████    | 6/10 [00:00<00:00, 15.70it/s, Loss=0.853]
+Epoch 555/10001: 100%|██████████| 10/10 [00:00<00:00, 14.02it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 556/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 556/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 556/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.851]
+Epoch 556/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.851]
+Epoch 556/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.852]
+Epoch 556/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.854]
+Epoch 556/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.848]
+Epoch 556/10001:  10%|█         | 1/10 [00:00<00:04,  2.21it/s, Loss=0.854]
+Epoch 556/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.854]
+Epoch 556/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.85] 
+Epoch 556/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.846]
+Epoch 556/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.846]
+Epoch 556/10001:  60%|██████    | 6/10 [00:00<00:00, 13.27it/s, Loss=0.852]
+Epoch 556/10001: 100%|██████████| 10/10 [00:00<00:00, 13.40it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 557/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 557/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 557/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.846]
+Epoch 557/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.848]
+Epoch 557/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.854]
+Epoch 557/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.851]
+Epoch 557/10001:  10%|█         | 1/10 [00:00<00:03,  2.37it/s, Loss=0.86] 
+Epoch 557/10001:  50%|█████     | 5/10 [00:00<00:00, 11.42it/s, Loss=0.86]
+Epoch 557/10001:  50%|█████     | 5/10 [00:00<00:00, 11.42it/s, Loss=0.857]
+Epoch 557/10001:  50%|█████     | 5/10 [00:00<00:00, 11.42it/s, Loss=0.851]
+Epoch 557/10001:  50%|█████     | 5/10 [00:00<00:00, 11.42it/s, Loss=0.853]
+Epoch 557/10001:  50%|█████     | 5/10 [00:00<00:00, 11.42it/s, Loss=0.849]
+Epoch 557/10001:  50%|█████     | 5/10 [00:00<00:00, 11.42it/s, Loss=0.861]
+Epoch 557/10001: 100%|██████████| 10/10 [00:00<00:00, 21.11it/s, Loss=0.861]
+Epoch 557/10001: 100%|██████████| 10/10 [00:00<00:00, 13.30it/s, Loss=0.861]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 558/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 558/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 558/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.854]
+Epoch 558/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.844]
+Epoch 558/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.857]
+Epoch 558/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.854]
+Epoch 558/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.846]
+Epoch 558/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.854]
+Epoch 558/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.853]
+Epoch 558/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.848]
+Epoch 558/10001:  80%|████████  | 8/10 [00:00<00:00, 18.87it/s, Loss=0.848]
+Epoch 558/10001:  80%|████████  | 8/10 [00:00<00:00, 18.87it/s, Loss=0.855]
+Epoch 558/10001:  80%|████████  | 8/10 [00:00<00:00, 18.87it/s, Loss=0.852]
+Epoch 558/10001: 100%|██████████| 10/10 [00:00<00:00, 14.79it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 559/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 559/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 559/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 559/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.861]
+Epoch 559/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.852]
+Epoch 559/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.859]
+Epoch 559/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.848]
+Epoch 559/10001:  50%|█████     | 5/10 [00:00<00:00, 11.11it/s, Loss=0.848]
+Epoch 559/10001:  50%|█████     | 5/10 [00:00<00:00, 11.11it/s, Loss=0.853]
+Epoch 559/10001:  50%|█████     | 5/10 [00:00<00:00, 11.11it/s, Loss=0.851]
+Epoch 559/10001:  50%|█████     | 5/10 [00:00<00:00, 11.11it/s, Loss=0.858]
+Epoch 559/10001:  50%|█████     | 5/10 [00:00<00:00, 11.11it/s, Loss=0.849]
+Epoch 559/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.34it/s, Loss=0.849]
+Epoch 559/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.34it/s, Loss=0.841]
+Epoch 559/10001: 100%|██████████| 10/10 [00:00<00:00, 12.48it/s, Loss=0.841]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 560/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 560/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 560/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.843]
+Epoch 560/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.849]
+Epoch 560/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.842]
+Epoch 560/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.845]
+Epoch 560/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.847]
+Epoch 560/10001:  10%|█         | 1/10 [00:00<00:04,  2.15it/s, Loss=0.864]
+Epoch 560/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.864]
+Epoch 560/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.85] 
+Epoch 560/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.847]
+Epoch 560/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.848]
+Epoch 560/10001:  60%|██████    | 6/10 [00:00<00:00, 13.10it/s, Loss=0.856]
+Epoch 560/10001: 100%|██████████| 10/10 [00:00<00:00, 13.08it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 561/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 561/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 561/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.852]
+Epoch 561/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.854]
+Epoch 561/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.853]
+Epoch 561/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.851]
+Epoch 561/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.849]
+Epoch 561/10001:  10%|█         | 1/10 [00:00<00:03,  2.34it/s, Loss=0.853]
+Epoch 561/10001:  60%|██████    | 6/10 [00:00<00:00, 14.23it/s, Loss=0.853]
+Epoch 561/10001:  60%|██████    | 6/10 [00:00<00:00, 14.23it/s, Loss=0.85] 
+Epoch 561/10001:  60%|██████    | 6/10 [00:00<00:00, 14.23it/s, Loss=0.85]
+Epoch 561/10001:  60%|██████    | 6/10 [00:00<00:00, 14.23it/s, Loss=0.853]
+Epoch 561/10001:  60%|██████    | 6/10 [00:00<00:00, 14.23it/s, Loss=0.84] 
+Epoch 561/10001: 100%|██████████| 10/10 [00:00<00:00, 13.89it/s, Loss=0.84]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 562/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 562/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 562/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.857]
+Epoch 562/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.856]
+Epoch 562/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.852]
+Epoch 562/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.848]
+Epoch 562/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.844]
+Epoch 562/10001:  10%|█         | 1/10 [00:00<00:03,  2.61it/s, Loss=0.858]
+Epoch 562/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.858]
+Epoch 562/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.856]
+Epoch 562/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.856]
+Epoch 562/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.843]
+Epoch 562/10001:  60%|██████    | 6/10 [00:00<00:00, 14.99it/s, Loss=0.855]
+Epoch 562/10001: 100%|██████████| 10/10 [00:00<00:00, 14.13it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 563/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 563/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.845]
+Epoch 563/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.845]
+Epoch 563/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.852]
+Epoch 563/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.853]
+Epoch 563/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.845]
+Epoch 563/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.849]
+Epoch 563/10001:  10%|█         | 1/10 [00:00<00:03,  2.92it/s, Loss=0.85] 
+Epoch 563/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.85]
+Epoch 563/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.852]
+Epoch 563/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.85] 
+Epoch 563/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.852]
+Epoch 563/10001:  60%|██████    | 6/10 [00:00<00:00, 16.14it/s, Loss=0.854]
+Epoch 563/10001: 100%|██████████| 10/10 [00:00<00:00, 14.83it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 564/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 564/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 564/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.855]
+Epoch 564/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.846]
+Epoch 564/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.855]
+Epoch 564/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.849]
+Epoch 564/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.854]
+Epoch 564/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.854]
+Epoch 564/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.855]
+Epoch 564/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.846]
+Epoch 564/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.855]
+Epoch 564/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.844]
+Epoch 564/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.857]
+Epoch 564/10001: 100%|██████████| 10/10 [00:00<00:00, 21.04it/s, Loss=0.857]
+Epoch 564/10001: 100%|██████████| 10/10 [00:00<00:00, 13.26it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 565/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 565/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 565/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.848]
+Epoch 565/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.848]
+Epoch 565/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.852]
+Epoch 565/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.849]
+Epoch 565/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.854]
+Epoch 565/10001:  10%|█         | 1/10 [00:00<00:03,  2.49it/s, Loss=0.851]
+Epoch 565/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.851]
+Epoch 565/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.851]
+Epoch 565/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.844]
+Epoch 565/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.854]
+Epoch 565/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.852]
+Epoch 565/10001: 100%|██████████| 10/10 [00:00<00:00, 20.69it/s, Loss=0.852]
+Epoch 565/10001: 100%|██████████| 10/10 [00:00<00:00, 13.56it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 566/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 566/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.842]
+Epoch 566/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.842]
+Epoch 566/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.857]
+Epoch 566/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.849]
+Epoch 566/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.847]
+Epoch 566/10001:  10%|█         | 1/10 [00:00<00:03,  2.95it/s, Loss=0.84] 
+Epoch 566/10001:  50%|█████     | 5/10 [00:00<00:00, 13.54it/s, Loss=0.84]
+Epoch 566/10001:  50%|█████     | 5/10 [00:00<00:00, 13.54it/s, Loss=0.856]
+Epoch 566/10001:  50%|█████     | 5/10 [00:00<00:00, 13.54it/s, Loss=0.857]
+Epoch 566/10001:  50%|█████     | 5/10 [00:00<00:00, 13.54it/s, Loss=0.85] 
+Epoch 566/10001:  50%|█████     | 5/10 [00:00<00:00, 13.54it/s, Loss=0.851]
+Epoch 566/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.62it/s, Loss=0.851]
+Epoch 566/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.62it/s, Loss=0.854]
+Epoch 566/10001: 100%|██████████| 10/10 [00:00<00:00, 14.19it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 567/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 567/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 567/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.857]
+Epoch 567/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.854]
+Epoch 567/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.855]
+Epoch 567/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.842]
+Epoch 567/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.846]
+Epoch 567/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.845]
+Epoch 567/10001:  10%|█         | 1/10 [00:00<00:04,  2.17it/s, Loss=0.85] 
+Epoch 567/10001:  70%|███████   | 7/10 [00:00<00:00, 15.61it/s, Loss=0.85]
+Epoch 567/10001:  70%|███████   | 7/10 [00:00<00:00, 15.61it/s, Loss=0.854]
+Epoch 567/10001:  70%|███████   | 7/10 [00:00<00:00, 15.61it/s, Loss=0.85] 
+Epoch 567/10001:  70%|███████   | 7/10 [00:00<00:00, 15.61it/s, Loss=0.848]
+Epoch 567/10001: 100%|██████████| 10/10 [00:00<00:00, 12.52it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 568/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 568/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 568/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.851]
+Epoch 568/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.847]
+Epoch 568/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.857]
+Epoch 568/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.849]
+Epoch 568/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.851]
+Epoch 568/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.858]
+Epoch 568/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.853]
+Epoch 568/10001:  70%|███████   | 7/10 [00:00<00:00, 15.76it/s, Loss=0.853]
+Epoch 568/10001:  70%|███████   | 7/10 [00:00<00:00, 15.76it/s, Loss=0.845]
+Epoch 568/10001:  70%|███████   | 7/10 [00:00<00:00, 15.76it/s, Loss=0.852]
+Epoch 568/10001:  70%|███████   | 7/10 [00:00<00:00, 15.76it/s, Loss=0.848]
+Epoch 568/10001: 100%|██████████| 10/10 [00:00<00:00, 13.67it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 569/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 569/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 569/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.85]
+Epoch 569/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.85]
+Epoch 569/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.845]
+Epoch 569/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.851]
+Epoch 569/10001:  10%|█         | 1/10 [00:00<00:03,  2.84it/s, Loss=0.855]
+Epoch 569/10001:  50%|█████     | 5/10 [00:00<00:00, 12.81it/s, Loss=0.855]
+Epoch 569/10001:  50%|█████     | 5/10 [00:00<00:00, 12.81it/s, Loss=0.847]
+Epoch 569/10001:  50%|█████     | 5/10 [00:00<00:00, 12.81it/s, Loss=0.847]
+Epoch 569/10001:  50%|█████     | 5/10 [00:00<00:00, 12.81it/s, Loss=0.852]
+Epoch 569/10001:  50%|█████     | 5/10 [00:00<00:00, 12.81it/s, Loss=0.852]
+Epoch 569/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.56it/s, Loss=0.852]
+Epoch 569/10001:  90%|█████████ | 9/10 [00:00<00:00, 19.56it/s, Loss=0.848]
+Epoch 569/10001: 100%|██████████| 10/10 [00:00<00:00, 13.82it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 570/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 570/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 570/10001:  10%|█         | 1/10 [00:00<00:05,  1.78it/s, Loss=0.852]
+Epoch 570/10001:  10%|█         | 1/10 [00:00<00:05,  1.78it/s, Loss=0.849]
+Epoch 570/10001:  10%|█         | 1/10 [00:00<00:05,  1.78it/s, Loss=0.854]
+Epoch 570/10001:  10%|█         | 1/10 [00:00<00:05,  1.78it/s, Loss=0.848]
+Epoch 570/10001:  10%|█         | 1/10 [00:00<00:05,  1.78it/s, Loss=0.849]
+Epoch 570/10001:  10%|█         | 1/10 [00:00<00:05,  1.78it/s, Loss=0.845]
+Epoch 570/10001:  10%|█         | 1/10 [00:00<00:05,  1.78it/s, Loss=0.854]
+Epoch 570/10001:  70%|███████   | 7/10 [00:00<00:00, 13.12it/s, Loss=0.854]
+Epoch 570/10001:  70%|███████   | 7/10 [00:00<00:00, 13.12it/s, Loss=0.857]
+Epoch 570/10001:  70%|███████   | 7/10 [00:00<00:00, 13.12it/s, Loss=0.848]
+Epoch 570/10001:  70%|███████   | 7/10 [00:00<00:00, 13.12it/s, Loss=0.855]
+Epoch 570/10001: 100%|██████████| 10/10 [00:00<00:00, 11.77it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 571/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 571/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 571/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.852]
+Epoch 571/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.854]
+Epoch 571/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.85] 
+Epoch 571/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.843]
+Epoch 571/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.847]
+Epoch 571/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.847]
+Epoch 571/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.851]
+Epoch 571/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.851]
+Epoch 571/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.85] 
+Epoch 571/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.845]
+Epoch 571/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.854]
+Epoch 571/10001: 100%|██████████| 10/10 [00:00<00:00, 14.52it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 572/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 572/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 572/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.849]
+Epoch 572/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.85] 
+Epoch 572/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.855]
+Epoch 572/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.857]
+Epoch 572/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.852]
+Epoch 572/10001:  50%|█████     | 5/10 [00:00<00:00, 13.71it/s, Loss=0.852]
+Epoch 572/10001:  50%|█████     | 5/10 [00:00<00:00, 13.71it/s, Loss=0.858]
+Epoch 572/10001:  50%|█████     | 5/10 [00:00<00:00, 13.71it/s, Loss=0.848]
+Epoch 572/10001:  50%|█████     | 5/10 [00:00<00:00, 13.71it/s, Loss=0.856]
+Epoch 572/10001:  50%|█████     | 5/10 [00:00<00:00, 13.71it/s, Loss=0.855]
+Epoch 572/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.20it/s, Loss=0.855]
+Epoch 572/10001:  90%|█████████ | 9/10 [00:00<00:00, 20.20it/s, Loss=0.853]
+Epoch 572/10001: 100%|██████████| 10/10 [00:00<00:00, 13.65it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 573/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 573/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 573/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.854]
+Epoch 573/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.852]
+Epoch 573/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.849]
+Epoch 573/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.855]
+Epoch 573/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.846]
+Epoch 573/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.847]
+Epoch 573/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.848]
+Epoch 573/10001:  10%|█         | 1/10 [00:00<00:03,  2.52it/s, Loss=0.856]
+Epoch 573/10001:  80%|████████  | 8/10 [00:00<00:00, 19.87it/s, Loss=0.856]
+Epoch 573/10001:  80%|████████  | 8/10 [00:00<00:00, 19.87it/s, Loss=0.842]
+Epoch 573/10001:  80%|████████  | 8/10 [00:00<00:00, 19.87it/s, Loss=0.854]
+Epoch 573/10001: 100%|██████████| 10/10 [00:00<00:00, 15.66it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 574/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 574/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 574/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.851]
+Epoch 574/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.851]
+Epoch 574/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.854]
+Epoch 574/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.844]
+Epoch 574/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.852]
+Epoch 574/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.853]
+Epoch 574/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.856]
+Epoch 574/10001:  10%|█         | 1/10 [00:00<00:03,  2.43it/s, Loss=0.857]
+Epoch 574/10001:  80%|████████  | 8/10 [00:00<00:00, 19.51it/s, Loss=0.857]
+Epoch 574/10001:  80%|████████  | 8/10 [00:00<00:00, 19.51it/s, Loss=0.863]
+Epoch 574/10001:  80%|████████  | 8/10 [00:00<00:00, 19.51it/s, Loss=0.853]
+Epoch 574/10001: 100%|██████████| 10/10 [00:00<00:00, 15.09it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 575/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 575/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 575/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.848]
+Epoch 575/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.848]
+Epoch 575/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.86] 
+Epoch 575/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.852]
+Epoch 575/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.853]
+Epoch 575/10001:  10%|█         | 1/10 [00:00<00:04,  2.22it/s, Loss=0.854]
+Epoch 575/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.854]
+Epoch 575/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.853]
+Epoch 575/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.856]
+Epoch 575/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.846]
+Epoch 575/10001:  60%|██████    | 6/10 [00:00<00:00, 13.37it/s, Loss=0.847]
+Epoch 575/10001: 100%|██████████| 10/10 [00:00<00:00, 13.65it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 576/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 576/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.844]
+Epoch 576/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.844]
+Epoch 576/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.849]
+Epoch 576/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.852]
+Epoch 576/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.845]
+Epoch 576/10001:  10%|█         | 1/10 [00:00<00:03,  2.75it/s, Loss=0.855]
+Epoch 576/10001:  50%|█████     | 5/10 [00:00<00:00, 13.19it/s, Loss=0.855]
+Epoch 576/10001:  50%|█████     | 5/10 [00:00<00:00, 13.19it/s, Loss=0.85] 
+Epoch 576/10001:  50%|█████     | 5/10 [00:00<00:00, 13.19it/s, Loss=0.85]
+Epoch 576/10001:  50%|█████     | 5/10 [00:00<00:00, 13.19it/s, Loss=0.854]
+Epoch 576/10001:  50%|█████     | 5/10 [00:00<00:00, 13.19it/s, Loss=0.848]
+Epoch 576/10001:  50%|█████     | 5/10 [00:00<00:00, 13.19it/s, Loss=0.848]
+Epoch 576/10001: 100%|██████████| 10/10 [00:00<00:00, 14.20it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 577/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 577/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 577/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.853]
+Epoch 577/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.847]
+Epoch 577/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.855]
+Epoch 577/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.849]
+Epoch 577/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.852]
+Epoch 577/10001:  50%|█████     | 5/10 [00:00<00:00, 10.60it/s, Loss=0.852]
+Epoch 577/10001:  50%|█████     | 5/10 [00:00<00:00, 10.60it/s, Loss=0.859]
+Epoch 577/10001:  50%|█████     | 5/10 [00:00<00:00, 10.60it/s, Loss=0.854]
+Epoch 577/10001:  50%|█████     | 5/10 [00:00<00:00, 10.60it/s, Loss=0.853]
+Epoch 577/10001:  50%|█████     | 5/10 [00:00<00:00, 10.60it/s, Loss=0.851]
+Epoch 577/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.40it/s, Loss=0.851]
+Epoch 577/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.40it/s, Loss=0.846]
+Epoch 577/10001: 100%|██████████| 10/10 [00:00<00:00, 11.82it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 578/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 578/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 578/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.849]
+Epoch 578/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.849]
+Epoch 578/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.85] 
+Epoch 578/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.851]
+Epoch 578/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.848]
+Epoch 578/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.849]
+Epoch 578/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.846]
+Epoch 578/10001:  70%|███████   | 7/10 [00:00<00:00, 14.85it/s, Loss=0.846]
+Epoch 578/10001:  70%|███████   | 7/10 [00:00<00:00, 14.85it/s, Loss=0.85] 
+Epoch 578/10001:  70%|███████   | 7/10 [00:00<00:00, 14.85it/s, Loss=0.854]
+Epoch 578/10001:  70%|███████   | 7/10 [00:00<00:00, 14.85it/s, Loss=0.857]
+Epoch 578/10001: 100%|██████████| 10/10 [00:00<00:00, 12.95it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 579/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 579/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 579/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.855]
+Epoch 579/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.849]
+Epoch 579/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.847]
+Epoch 579/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.849]
+Epoch 579/10001:  10%|█         | 1/10 [00:00<00:03,  2.30it/s, Loss=0.854]
+Epoch 579/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.854]
+Epoch 579/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.852]
+Epoch 579/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.855]
+Epoch 579/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.838]
+Epoch 579/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.856]
+Epoch 579/10001:  50%|█████     | 5/10 [00:00<00:00, 11.16it/s, Loss=0.857]
+Epoch 579/10001: 100%|██████████| 10/10 [00:00<00:00, 20.83it/s, Loss=0.857]
+Epoch 579/10001: 100%|██████████| 10/10 [00:00<00:00, 12.91it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 580/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 580/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 580/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.854]
+Epoch 580/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.855]
+Epoch 580/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.858]
+Epoch 580/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.857]
+Epoch 580/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.848]
+Epoch 580/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.856]
+Epoch 580/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.856]
+Epoch 580/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.853]
+Epoch 580/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.856]
+Epoch 580/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.856]
+Epoch 580/10001:  60%|██████    | 6/10 [00:00<00:00, 14.65it/s, Loss=0.845]
+Epoch 580/10001: 100%|██████████| 10/10 [00:00<00:00, 14.60it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 581/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 581/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.846]
+Epoch 581/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.846]
+Epoch 581/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.848]
+Epoch 581/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.851]
+Epoch 581/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.853]
+Epoch 581/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.858]
+Epoch 581/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.857]
+Epoch 581/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.847]
+Epoch 581/10001:  70%|███████   | 7/10 [00:00<00:00, 16.83it/s, Loss=0.847]
+Epoch 581/10001:  70%|███████   | 7/10 [00:00<00:00, 16.83it/s, Loss=0.853]
+Epoch 581/10001:  70%|███████   | 7/10 [00:00<00:00, 16.83it/s, Loss=0.852]
+Epoch 581/10001:  70%|███████   | 7/10 [00:00<00:00, 16.83it/s, Loss=0.852]
+Epoch 581/10001: 100%|██████████| 10/10 [00:00<00:00, 13.87it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 582/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 582/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 582/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.848]
+Epoch 582/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.846]
+Epoch 582/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 582/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.852]
+Epoch 582/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.852]
+Epoch 582/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.851]
+Epoch 582/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.854]
+Epoch 582/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.842]
+Epoch 582/10001:  40%|████      | 4/10 [00:00<00:00,  9.11it/s, Loss=0.849]
+Epoch 582/10001:  80%|████████  | 8/10 [00:00<00:00, 16.63it/s, Loss=0.849]
+Epoch 582/10001:  80%|████████  | 8/10 [00:00<00:00, 16.63it/s, Loss=0.848]
+Epoch 582/10001:  80%|████████  | 8/10 [00:00<00:00, 16.63it/s, Loss=0.845]
+Epoch 582/10001: 100%|██████████| 10/10 [00:00<00:00, 11.83it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 583/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 583/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 583/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.85]
+Epoch 583/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.85]
+Epoch 583/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 583/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.85] 
+Epoch 583/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.857]
+Epoch 583/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.855]
+Epoch 583/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 583/10001:  70%|███████   | 7/10 [00:00<00:00, 15.71it/s, Loss=0.853]
+Epoch 583/10001:  70%|███████   | 7/10 [00:00<00:00, 15.71it/s, Loss=0.85] 
+Epoch 583/10001:  70%|███████   | 7/10 [00:00<00:00, 15.71it/s, Loss=0.854]
+Epoch 583/10001:  70%|███████   | 7/10 [00:00<00:00, 15.71it/s, Loss=0.856]
+Epoch 583/10001: 100%|██████████| 10/10 [00:00<00:00, 13.68it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 584/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 584/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 584/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.85]
+Epoch 584/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.855]
+Epoch 584/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.851]
+Epoch 584/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.85] 
+Epoch 584/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.847]
+Epoch 584/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 584/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.854]
+Epoch 584/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.857]
+Epoch 584/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.846]
+Epoch 584/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.856]
+Epoch 584/10001:  60%|██████    | 6/10 [00:00<00:00, 13.97it/s, Loss=0.846]
+Epoch 584/10001: 100%|██████████| 10/10 [00:00<00:00, 13.93it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 585/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 585/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 585/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.852]
+Epoch 585/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.855]
+Epoch 585/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.853]
+Epoch 585/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.849]
+Epoch 585/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.859]
+Epoch 585/10001:  10%|█         | 1/10 [00:00<00:03,  2.28it/s, Loss=0.855]
+Epoch 585/10001:  60%|██████    | 6/10 [00:00<00:00, 13.73it/s, Loss=0.855]
+Epoch 585/10001:  60%|██████    | 6/10 [00:00<00:00, 13.73it/s, Loss=0.84] 
+Epoch 585/10001:  60%|██████    | 6/10 [00:00<00:00, 13.73it/s, Loss=0.846]
+Epoch 585/10001:  60%|██████    | 6/10 [00:00<00:00, 13.73it/s, Loss=0.85] 
+Epoch 585/10001:  60%|██████    | 6/10 [00:00<00:00, 13.73it/s, Loss=0.843]
+Epoch 585/10001: 100%|██████████| 10/10 [00:00<00:00, 13.62it/s, Loss=0.843]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 586/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 586/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 586/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.847]
+Epoch 586/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.854]
+Epoch 586/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.851]
+Epoch 586/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.851]
+Epoch 586/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.842]
+Epoch 586/10001:  10%|█         | 1/10 [00:00<00:03,  2.90it/s, Loss=0.844]
+Epoch 586/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.844]
+Epoch 586/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.852]
+Epoch 586/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.855]
+Epoch 586/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.845]
+Epoch 586/10001:  60%|██████    | 6/10 [00:00<00:00, 16.64it/s, Loss=0.847]
+Epoch 586/10001: 100%|██████████| 10/10 [00:00<00:00, 16.17it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 587/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 587/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 587/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.847]
+Epoch 587/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.854]
+Epoch 587/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.849]
+Epoch 587/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.85] 
+Epoch 587/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.852]
+Epoch 587/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.852]
+Epoch 587/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.849]
+Epoch 587/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.845]
+Epoch 587/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.848]
+Epoch 587/10001:  50%|█████     | 5/10 [00:00<00:00, 12.51it/s, Loss=0.854]
+Epoch 587/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.87it/s, Loss=0.854]
+Epoch 587/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.87it/s, Loss=0.851]
+Epoch 587/10001: 100%|██████████| 10/10 [00:00<00:00, 13.20it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 588/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 588/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 588/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.847]
+Epoch 588/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.85] 
+Epoch 588/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.853]
+Epoch 588/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 588/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.853]
+Epoch 588/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.853]
+Epoch 588/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.853]
+Epoch 588/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.847]
+Epoch 588/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.848]
+Epoch 588/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.851]
+Epoch 588/10001:  50%|█████     | 5/10 [00:00<00:00, 11.09it/s, Loss=0.846]
+Epoch 588/10001: 100%|██████████| 10/10 [00:00<00:00, 19.86it/s, Loss=0.846]
+Epoch 588/10001: 100%|██████████| 10/10 [00:00<00:00, 12.48it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 589/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 589/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 589/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.854]
+Epoch 589/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.848]
+Epoch 589/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.857]
+Epoch 589/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.847]
+Epoch 589/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.845]
+Epoch 589/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.853]
+Epoch 589/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.853]
+Epoch 589/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.844]
+Epoch 589/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.85] 
+Epoch 589/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.848]
+Epoch 589/10001:  60%|██████    | 6/10 [00:00<00:00, 13.81it/s, Loss=0.847]
+Epoch 589/10001: 100%|██████████| 10/10 [00:00<00:00, 13.23it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 590/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 590/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 590/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.847]
+Epoch 590/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.856]
+Epoch 590/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.852]
+Epoch 590/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.848]
+Epoch 590/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.845]
+Epoch 590/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.852]
+Epoch 590/10001:  10%|█         | 1/10 [00:00<00:04,  1.91it/s, Loss=0.847]
+Epoch 590/10001:  70%|███████   | 7/10 [00:00<00:00, 14.29it/s, Loss=0.847]
+Epoch 590/10001:  70%|███████   | 7/10 [00:00<00:00, 14.29it/s, Loss=0.84] 
+Epoch 590/10001:  70%|███████   | 7/10 [00:00<00:00, 14.29it/s, Loss=0.859]
+Epoch 590/10001:  70%|███████   | 7/10 [00:00<00:00, 14.29it/s, Loss=0.846]
+Epoch 590/10001: 100%|██████████| 10/10 [00:00<00:00, 12.45it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 591/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 591/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 591/10001:  10%|█         | 1/10 [00:00<00:04,  1.98it/s, Loss=0.854]
+Epoch 591/10001:  10%|█         | 1/10 [00:00<00:04,  1.98it/s, Loss=0.848]
+Epoch 591/10001:  10%|█         | 1/10 [00:00<00:04,  1.98it/s, Loss=0.841]
+Epoch 591/10001:  10%|█         | 1/10 [00:00<00:04,  1.98it/s, Loss=0.848]
+Epoch 591/10001:  10%|█         | 1/10 [00:00<00:04,  1.98it/s, Loss=0.848]
+Epoch 591/10001:  10%|█         | 1/10 [00:00<00:04,  1.98it/s, Loss=0.855]
+Epoch 591/10001:  10%|█         | 1/10 [00:00<00:04,  1.98it/s, Loss=0.847]
+Epoch 591/10001:  10%|█         | 1/10 [00:00<00:04,  1.98it/s, Loss=0.844]
+Epoch 591/10001:  10%|█         | 1/10 [00:00<00:04,  1.98it/s, Loss=0.854]
+Epoch 591/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.26it/s, Loss=0.854]
+Epoch 591/10001:  90%|█████████ | 9/10 [00:00<00:00, 18.26it/s, Loss=0.845]
+Epoch 591/10001: 100%|██████████| 10/10 [00:00<00:00, 13.23it/s, Loss=0.845]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 592/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 592/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 592/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.849]
+Epoch 592/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.846]
+Epoch 592/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.847]
+Epoch 592/10001:  10%|█         | 1/10 [00:00<00:03,  2.39it/s, Loss=0.848]
+Epoch 592/10001:  40%|████      | 4/10 [00:00<00:00,  9.35it/s, Loss=0.848]
+Epoch 592/10001:  40%|████      | 4/10 [00:00<00:00,  9.35it/s, Loss=0.853]
+Epoch 592/10001:  40%|████      | 4/10 [00:00<00:00,  9.35it/s, Loss=0.849]
+Epoch 592/10001:  40%|████      | 4/10 [00:00<00:00,  9.35it/s, Loss=0.847]
+Epoch 592/10001:  40%|████      | 4/10 [00:00<00:00,  9.35it/s, Loss=0.854]
+Epoch 592/10001:  80%|████████  | 8/10 [00:00<00:00, 17.09it/s, Loss=0.854]
+Epoch 592/10001:  80%|████████  | 8/10 [00:00<00:00, 17.09it/s, Loss=0.855]
+Epoch 592/10001:  80%|████████  | 8/10 [00:00<00:00, 17.09it/s, Loss=0.85] 
+Epoch 592/10001: 100%|██████████| 10/10 [00:00<00:00, 12.31it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 593/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 593/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 593/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.85]
+Epoch 593/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.856]
+Epoch 593/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.855]
+Epoch 593/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.862]
+Epoch 593/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.86] 
+Epoch 593/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.851]
+Epoch 593/10001:  10%|█         | 1/10 [00:00<00:03,  2.31it/s, Loss=0.846]
+Epoch 593/10001:  70%|███████   | 7/10 [00:00<00:00, 16.35it/s, Loss=0.846]
+Epoch 593/10001:  70%|███████   | 7/10 [00:00<00:00, 16.35it/s, Loss=0.851]
+Epoch 593/10001:  70%|███████   | 7/10 [00:00<00:00, 16.35it/s, Loss=0.854]
+Epoch 593/10001:  70%|███████   | 7/10 [00:00<00:00, 16.35it/s, Loss=0.849]
+Epoch 593/10001: 100%|██████████| 10/10 [00:00<00:00, 13.70it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 594/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 594/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 594/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.851]
+Epoch 594/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.852]
+Epoch 594/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.85] 
+Epoch 594/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.849]
+Epoch 594/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.858]
+Epoch 594/10001:  10%|█         | 1/10 [00:00<00:04,  2.10it/s, Loss=0.846]
+Epoch 594/10001:  60%|██████    | 6/10 [00:00<00:00, 12.71it/s, Loss=0.846]
+Epoch 594/10001:  60%|██████    | 6/10 [00:00<00:00, 12.71it/s, Loss=0.85] 
+Epoch 594/10001:  60%|██████    | 6/10 [00:00<00:00, 12.71it/s, Loss=0.853]
+Epoch 594/10001:  60%|██████    | 6/10 [00:00<00:00, 12.71it/s, Loss=0.85] 
+Epoch 594/10001:  60%|██████    | 6/10 [00:00<00:00, 12.71it/s, Loss=0.85]
+Epoch 594/10001: 100%|██████████| 10/10 [00:00<00:00, 12.32it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 595/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 595/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 595/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.85]
+Epoch 595/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.864]
+Epoch 595/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.853]
+Epoch 595/10001:  10%|█         | 1/10 [00:00<00:04,  2.23it/s, Loss=0.852]
+Epoch 595/10001:  40%|████      | 4/10 [00:00<00:00,  8.94it/s, Loss=0.852]
+Epoch 595/10001:  40%|████      | 4/10 [00:00<00:00,  8.94it/s, Loss=0.843]
+Epoch 595/10001:  40%|████      | 4/10 [00:00<00:00,  8.94it/s, Loss=0.852]
+Epoch 595/10001:  40%|████      | 4/10 [00:00<00:00,  8.94it/s, Loss=0.852]
+Epoch 595/10001:  40%|████      | 4/10 [00:00<00:00,  8.94it/s, Loss=0.849]
+Epoch 595/10001:  80%|████████  | 8/10 [00:00<00:00, 16.51it/s, Loss=0.849]
+Epoch 595/10001:  80%|████████  | 8/10 [00:00<00:00, 16.51it/s, Loss=0.851]
+Epoch 595/10001:  80%|████████  | 8/10 [00:00<00:00, 16.51it/s, Loss=0.85] 
+Epoch 595/10001: 100%|██████████| 10/10 [00:00<00:00, 11.98it/s, Loss=0.85]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 596/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 596/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 596/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.85]
+Epoch 596/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 596/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.849]
+Epoch 596/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.854]
+Epoch 596/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.855]
+Epoch 596/10001:  10%|█         | 1/10 [00:00<00:03,  2.32it/s, Loss=0.857]
+Epoch 596/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.857]
+Epoch 596/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.847]
+Epoch 596/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.846]
+Epoch 596/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.853]
+Epoch 596/10001:  60%|██████    | 6/10 [00:00<00:00, 13.69it/s, Loss=0.856]
+Epoch 596/10001: 100%|██████████| 10/10 [00:00<00:00, 19.89it/s, Loss=0.856]
+Epoch 596/10001: 100%|██████████| 10/10 [00:00<00:00, 12.86it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 597/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 597/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 597/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.851]
+Epoch 597/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.856]
+Epoch 597/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.851]
+Epoch 597/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.848]
+Epoch 597/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 597/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.856]
+Epoch 597/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 597/10001:  70%|███████   | 7/10 [00:00<00:00, 15.90it/s, Loss=0.853]
+Epoch 597/10001:  70%|███████   | 7/10 [00:00<00:00, 15.90it/s, Loss=0.854]
+Epoch 597/10001:  70%|███████   | 7/10 [00:00<00:00, 15.90it/s, Loss=0.846]
+Epoch 597/10001:  70%|███████   | 7/10 [00:00<00:00, 15.90it/s, Loss=0.853]
+Epoch 597/10001: 100%|██████████| 10/10 [00:00<00:00, 13.12it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 598/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 598/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 598/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.855]
+Epoch 598/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.852]
+Epoch 598/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.849]
+Epoch 598/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.855]
+Epoch 598/10001:  10%|█         | 1/10 [00:00<00:03,  2.57it/s, Loss=0.847]
+Epoch 598/10001:  50%|█████     | 5/10 [00:00<00:00, 11.92it/s, Loss=0.847]
+Epoch 598/10001:  50%|█████     | 5/10 [00:00<00:00, 11.92it/s, Loss=0.849]
+Epoch 598/10001:  50%|█████     | 5/10 [00:00<00:00, 11.92it/s, Loss=0.856]
+Epoch 598/10001:  50%|█████     | 5/10 [00:00<00:00, 11.92it/s, Loss=0.846]
+Epoch 598/10001:  50%|█████     | 5/10 [00:00<00:00, 11.92it/s, Loss=0.859]
+Epoch 598/10001:  50%|█████     | 5/10 [00:00<00:00, 11.92it/s, Loss=0.848]
+Epoch 598/10001: 100%|██████████| 10/10 [00:00<00:00, 21.12it/s, Loss=0.848]
+Epoch 598/10001: 100%|██████████| 10/10 [00:00<00:00, 12.85it/s, Loss=0.848]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 599/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 599/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 599/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.85]
+Epoch 599/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.857]
+Epoch 599/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.848]
+Epoch 599/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.846]
+Epoch 599/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.849]
+Epoch 599/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.852]
+Epoch 599/10001:  10%|█         | 1/10 [00:00<00:03,  2.74it/s, Loss=0.85] 
+Epoch 599/10001:  70%|███████   | 7/10 [00:00<00:00, 18.09it/s, Loss=0.85]
+Epoch 599/10001:  70%|███████   | 7/10 [00:00<00:00, 18.09it/s, Loss=0.848]
+Epoch 599/10001:  70%|███████   | 7/10 [00:00<00:00, 18.09it/s, Loss=0.851]
+Epoch 599/10001:  70%|███████   | 7/10 [00:00<00:00, 18.09it/s, Loss=0.851]
+Epoch 599/10001: 100%|██████████| 10/10 [00:00<00:00, 15.04it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 600/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 600/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.848]
+Epoch 600/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.848]
+Epoch 600/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.851]
+Epoch 600/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.857]
+Epoch 600/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.858]
+Epoch 600/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.857]
+Epoch 600/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.845]
+Epoch 600/10001:  10%|█         | 1/10 [00:00<00:03,  2.72it/s, Loss=0.848]
+Epoch 600/10001:  70%|███████   | 7/10 [00:00<00:00, 18.50it/s, Loss=0.848]
+Epoch 600/10001:  70%|███████   | 7/10 [00:00<00:00, 18.50it/s, Loss=0.852]
+Epoch 600/10001:  70%|███████   | 7/10 [00:00<00:00, 18.50it/s, Loss=0.852]
+Epoch 600/10001:  70%|███████   | 7/10 [00:00<00:00, 18.50it/s, Loss=0.854]
+Epoch 600/10001: 100%|██████████| 10/10 [00:00<00:00, 15.33it/s, Loss=0.854]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 601/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 601/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 601/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.852]
+Epoch 601/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.847]
+Epoch 601/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.851]
+Epoch 601/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.852]
+Epoch 601/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.846]
+Epoch 601/10001:  10%|█         | 1/10 [00:00<00:04,  2.11it/s, Loss=0.845]
+Epoch 601/10001:  60%|██████    | 6/10 [00:00<00:00, 12.76it/s, Loss=0.845]
+Epoch 601/10001:  60%|██████    | 6/10 [00:00<00:00, 12.76it/s, Loss=0.851]
+Epoch 601/10001:  60%|██████    | 6/10 [00:00<00:00, 12.76it/s, Loss=0.849]
+Epoch 601/10001:  60%|██████    | 6/10 [00:00<00:00, 12.76it/s, Loss=0.846]
+Epoch 601/10001:  60%|██████    | 6/10 [00:00<00:00, 12.76it/s, Loss=0.856]
+Epoch 601/10001: 100%|██████████| 10/10 [00:00<00:00, 12.35it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 602/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 602/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 602/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.854]
+Epoch 602/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.845]
+Epoch 602/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.852]
+Epoch 602/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.853]
+Epoch 602/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.853]
+Epoch 602/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.852]
+Epoch 602/10001:  10%|█         | 1/10 [00:00<00:04,  2.25it/s, Loss=0.846]
+Epoch 602/10001:  70%|███████   | 7/10 [00:00<00:00, 15.90it/s, Loss=0.846]
+Epoch 602/10001:  70%|███████   | 7/10 [00:00<00:00, 15.90it/s, Loss=0.851]
+Epoch 602/10001:  70%|███████   | 7/10 [00:00<00:00, 15.90it/s, Loss=0.845]
+Epoch 602/10001:  70%|███████   | 7/10 [00:00<00:00, 15.90it/s, Loss=0.86] 
+Epoch 602/10001: 100%|██████████| 10/10 [00:00<00:00, 13.85it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 603/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 603/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.857]
+Epoch 603/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.857]
+Epoch 603/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.846]
+Epoch 603/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.854]
+Epoch 603/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.856]
+Epoch 603/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.855]
+Epoch 603/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.853]
+Epoch 603/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.846]
+Epoch 603/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.848]
+Epoch 603/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.855]
+Epoch 603/10001:  90%|█████████ | 9/10 [00:00<00:00, 21.25it/s, Loss=0.855]
+Epoch 603/10001:  90%|█████████ | 9/10 [00:00<00:00, 21.25it/s, Loss=0.847]
+Epoch 603/10001: 100%|██████████| 10/10 [00:00<00:00, 15.14it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 604/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 604/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.847]
+Epoch 604/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.847]
+Epoch 604/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.849]
+Epoch 604/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.863]
+Epoch 604/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 604/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.848]
+Epoch 604/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.848]
+Epoch 604/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.851]
+Epoch 604/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.845]
+Epoch 604/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.855]
+Epoch 604/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.853]
+Epoch 604/10001:  50%|█████     | 5/10 [00:00<00:00, 11.72it/s, Loss=0.86] 
+Epoch 604/10001: 100%|██████████| 10/10 [00:00<00:00, 20.68it/s, Loss=0.86]
+Epoch 604/10001: 100%|██████████| 10/10 [00:00<00:00, 13.26it/s, Loss=0.86]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 605/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 605/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.854]
+Epoch 605/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.854]
+Epoch 605/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.855]
+Epoch 605/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.856]
+Epoch 605/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.851]
+Epoch 605/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.851]
+Epoch 605/10001:  10%|█         | 1/10 [00:00<00:03,  2.40it/s, Loss=0.856]
+Epoch 605/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.856]
+Epoch 605/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.859]
+Epoch 605/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.853]
+Epoch 605/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.842]
+Epoch 605/10001:  60%|██████    | 6/10 [00:00<00:00, 14.43it/s, Loss=0.853]
+Epoch 605/10001: 100%|██████████| 10/10 [00:00<00:00, 14.30it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 606/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 606/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.844]
+Epoch 606/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.844]
+Epoch 606/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.85] 
+Epoch 606/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.848]
+Epoch 606/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.852]
+Epoch 606/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.855]
+Epoch 606/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.85] 
+Epoch 606/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.85]
+Epoch 606/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.853]
+Epoch 606/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.851]
+Epoch 606/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.85] 
+Epoch 606/10001:  60%|██████    | 6/10 [00:00<00:00, 16.40it/s, Loss=0.846]
+Epoch 606/10001: 100%|██████████| 10/10 [00:00<00:00, 15.59it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 607/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 607/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.86]
+Epoch 607/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.86]
+Epoch 607/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.85]
+Epoch 607/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.86]
+Epoch 607/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.851]
+Epoch 607/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.855]
+Epoch 607/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.851]
+Epoch 607/10001:  10%|█         | 1/10 [00:00<00:02,  3.01it/s, Loss=0.849]
+Epoch 607/10001:  70%|███████   | 7/10 [00:00<00:00, 19.72it/s, Loss=0.849]
+Epoch 607/10001:  70%|███████   | 7/10 [00:00<00:00, 19.72it/s, Loss=0.852]
+Epoch 607/10001:  70%|███████   | 7/10 [00:00<00:00, 19.72it/s, Loss=0.853]
+Epoch 607/10001:  70%|███████   | 7/10 [00:00<00:00, 19.72it/s, Loss=0.852]
+Epoch 607/10001: 100%|██████████| 10/10 [00:00<00:00, 15.86it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 608/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 608/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.843]
+Epoch 608/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.843]
+Epoch 608/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.861]
+Epoch 608/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.854]
+Epoch 608/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.856]
+Epoch 608/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.845]
+Epoch 608/10001:  10%|█         | 1/10 [00:00<00:03,  2.58it/s, Loss=0.851]
+Epoch 608/10001:  60%|██████    | 6/10 [00:00<00:00, 14.92it/s, Loss=0.851]
+Epoch 608/10001:  60%|██████    | 6/10 [00:00<00:00, 14.92it/s, Loss=0.844]
+Epoch 608/10001:  60%|██████    | 6/10 [00:00<00:00, 14.92it/s, Loss=0.861]
+Epoch 608/10001:  60%|██████    | 6/10 [00:00<00:00, 14.92it/s, Loss=0.851]
+Epoch 608/10001:  60%|██████    | 6/10 [00:00<00:00, 14.92it/s, Loss=0.837]
+Epoch 608/10001: 100%|██████████| 10/10 [00:00<00:00, 14.48it/s, Loss=0.837]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 609/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 609/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 609/10001:  10%|█         | 1/10 [00:00<00:04,  1.96it/s, Loss=0.853]
+Epoch 609/10001:  10%|█         | 1/10 [00:00<00:04,  1.96it/s, Loss=0.856]
+Epoch 609/10001:  10%|█         | 1/10 [00:00<00:04,  1.96it/s, Loss=0.845]
+Epoch 609/10001:  10%|█         | 1/10 [00:00<00:04,  1.96it/s, Loss=0.848]
+Epoch 609/10001:  10%|█         | 1/10 [00:00<00:04,  1.96it/s, Loss=0.86] 
+Epoch 609/10001:  10%|█         | 1/10 [00:00<00:04,  1.96it/s, Loss=0.846]
+Epoch 609/10001:  10%|█         | 1/10 [00:00<00:04,  1.96it/s, Loss=0.845]
+Epoch 609/10001:  70%|███████   | 7/10 [00:00<00:00, 14.33it/s, Loss=0.845]
+Epoch 609/10001:  70%|███████   | 7/10 [00:00<00:00, 14.33it/s, Loss=0.848]
+Epoch 609/10001:  70%|███████   | 7/10 [00:00<00:00, 14.33it/s, Loss=0.85] 
+Epoch 609/10001:  70%|███████   | 7/10 [00:00<00:00, 14.33it/s, Loss=0.849]
+Epoch 609/10001: 100%|██████████| 10/10 [00:00<00:00, 13.00it/s, Loss=0.849]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 610/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 610/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 610/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.851]
+Epoch 610/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.858]
+Epoch 610/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.844]
+Epoch 610/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.85] 
+Epoch 610/10001:  10%|█         | 1/10 [00:00<00:04,  2.14it/s, Loss=0.85]
+Epoch 610/10001:  50%|█████     | 5/10 [00:00<00:00, 10.56it/s, Loss=0.85]
+Epoch 610/10001:  50%|█████     | 5/10 [00:00<00:00, 10.56it/s, Loss=0.862]
+Epoch 610/10001:  50%|█████     | 5/10 [00:00<00:00, 10.56it/s, Loss=0.852]
+Epoch 610/10001:  50%|█████     | 5/10 [00:00<00:00, 10.56it/s, Loss=0.857]
+Epoch 610/10001:  50%|█████     | 5/10 [00:00<00:00, 10.56it/s, Loss=0.851]
+Epoch 610/10001:  50%|█████     | 5/10 [00:00<00:00, 10.56it/s, Loss=0.851]
+Epoch 610/10001: 100%|██████████| 10/10 [00:00<00:00, 19.59it/s, Loss=0.851]
+Epoch 610/10001: 100%|██████████| 10/10 [00:00<00:00, 12.41it/s, Loss=0.851]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 611/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 611/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 611/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.849]
+Epoch 611/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.849]
+Epoch 611/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.845]
+Epoch 611/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.851]
+Epoch 611/10001:  10%|█         | 1/10 [00:00<00:03,  2.98it/s, Loss=0.86] 
+Epoch 611/10001:  50%|█████     | 5/10 [00:00<00:00, 13.05it/s, Loss=0.86]
+Epoch 611/10001:  50%|█████     | 5/10 [00:00<00:00, 13.05it/s, Loss=0.851]
+Epoch 611/10001:  50%|█████     | 5/10 [00:00<00:00, 13.05it/s, Loss=0.848]
+Epoch 611/10001:  50%|█████     | 5/10 [00:00<00:00, 13.05it/s, Loss=0.849]
+Epoch 611/10001:  50%|█████     | 5/10 [00:00<00:00, 13.05it/s, Loss=0.85] 
+Epoch 611/10001:  50%|█████     | 5/10 [00:00<00:00, 13.05it/s, Loss=0.852]
+Epoch 611/10001: 100%|██████████| 10/10 [00:00<00:00, 22.41it/s, Loss=0.852]
+Epoch 611/10001: 100%|██████████| 10/10 [00:00<00:00, 14.52it/s, Loss=0.852]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 612/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 612/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 612/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.853]
+Epoch 612/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.853]
+Epoch 612/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.854]
+Epoch 612/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.849]
+Epoch 612/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.852]
+Epoch 612/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.848]
+Epoch 612/10001:  10%|█         | 1/10 [00:00<00:03,  2.88it/s, Loss=0.853]
+Epoch 612/10001:  70%|███████   | 7/10 [00:00<00:00, 18.55it/s, Loss=0.853]
+Epoch 612/10001:  70%|███████   | 7/10 [00:00<00:00, 18.55it/s, Loss=0.851]
+Epoch 612/10001:  70%|███████   | 7/10 [00:00<00:00, 18.55it/s, Loss=0.858]
+Epoch 612/10001:  70%|███████   | 7/10 [00:00<00:00, 18.55it/s, Loss=0.847]
+Epoch 612/10001: 100%|██████████| 10/10 [00:00<00:00, 15.68it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 613/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 613/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 613/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.852]
+Epoch 613/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.852]
+Epoch 613/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.853]
+Epoch 613/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.843]
+Epoch 613/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.85] 
+Epoch 613/10001:  10%|█         | 1/10 [00:00<00:03,  2.35it/s, Loss=0.851]
+Epoch 613/10001:  60%|██████    | 6/10 [00:00<00:00, 13.85it/s, Loss=0.851]
+Epoch 613/10001:  60%|██████    | 6/10 [00:00<00:00, 13.85it/s, Loss=0.854]
+Epoch 613/10001:  60%|██████    | 6/10 [00:00<00:00, 13.85it/s, Loss=0.856]
+Epoch 613/10001:  60%|██████    | 6/10 [00:00<00:00, 13.85it/s, Loss=0.853]
+Epoch 613/10001:  60%|██████    | 6/10 [00:00<00:00, 13.85it/s, Loss=0.855]
+Epoch 613/10001: 100%|██████████| 10/10 [00:00<00:00, 13.42it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 614/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 614/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 614/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.852]
+Epoch 614/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.856]
+Epoch 614/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.852]
+Epoch 614/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.844]
+Epoch 614/10001:  10%|█         | 1/10 [00:00<00:02,  3.19it/s, Loss=0.852]
+Epoch 614/10001:  50%|█████     | 5/10 [00:00<00:00, 14.34it/s, Loss=0.852]
+Epoch 614/10001:  50%|█████     | 5/10 [00:00<00:00, 14.34it/s, Loss=0.854]
+Epoch 614/10001:  50%|█████     | 5/10 [00:00<00:00, 14.34it/s, Loss=0.846]
+Epoch 614/10001:  50%|█████     | 5/10 [00:00<00:00, 14.34it/s, Loss=0.854]
+Epoch 614/10001:  50%|█████     | 5/10 [00:00<00:00, 14.34it/s, Loss=0.85] 
+Epoch 614/10001:  90%|█████████ | 9/10 [00:00<00:00, 21.50it/s, Loss=0.85]
+Epoch 614/10001:  90%|█████████ | 9/10 [00:00<00:00, 21.50it/s, Loss=0.859]
+Epoch 614/10001: 100%|██████████| 10/10 [00:00<00:00, 15.00it/s, Loss=0.859]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 615/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 615/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 615/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.852]
+Epoch 615/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.854]
+Epoch 615/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.85] 
+Epoch 615/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.847]
+Epoch 615/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.851]
+Epoch 615/10001:  10%|█         | 1/10 [00:00<00:03,  2.82it/s, Loss=0.857]
+Epoch 615/10001:  60%|██████    | 6/10 [00:00<00:00, 16.23it/s, Loss=0.857]
+Epoch 615/10001:  60%|██████    | 6/10 [00:00<00:00, 16.23it/s, Loss=0.851]
+Epoch 615/10001:  60%|██████    | 6/10 [00:00<00:00, 16.23it/s, Loss=0.849]
+Epoch 615/10001:  60%|██████    | 6/10 [00:00<00:00, 16.23it/s, Loss=0.844]
+Epoch 615/10001:  60%|██████    | 6/10 [00:00<00:00, 16.23it/s, Loss=0.855]
+Epoch 615/10001: 100%|██████████| 10/10 [00:00<00:00, 15.61it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 616/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 616/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 616/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.85]
+Epoch 616/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.85]
+Epoch 616/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.852]
+Epoch 616/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.85] 
+Epoch 616/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.853]
+Epoch 616/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.849]
+Epoch 616/10001:  10%|█         | 1/10 [00:00<00:04,  2.24it/s, Loss=0.847]
+Epoch 616/10001:  70%|███████   | 7/10 [00:00<00:00, 16.00it/s, Loss=0.847]
+Epoch 616/10001:  70%|███████   | 7/10 [00:00<00:00, 16.00it/s, Loss=0.854]
+Epoch 616/10001:  70%|███████   | 7/10 [00:00<00:00, 16.00it/s, Loss=0.85] 
+Epoch 616/10001:  70%|███████   | 7/10 [00:00<00:00, 16.00it/s, Loss=0.855]
+Epoch 616/10001: 100%|██████████| 10/10 [00:00<00:00, 13.85it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 617/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 617/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 617/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.852]
+Epoch 617/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.864]
+Epoch 617/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.846]
+Epoch 617/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.845]
+Epoch 617/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.853]
+Epoch 617/10001:  10%|█         | 1/10 [00:00<00:03,  2.33it/s, Loss=0.847]
+Epoch 617/10001:  60%|██████    | 6/10 [00:00<00:00, 14.13it/s, Loss=0.847]
+Epoch 617/10001:  60%|██████    | 6/10 [00:00<00:00, 14.13it/s, Loss=0.851]
+Epoch 617/10001:  60%|██████    | 6/10 [00:00<00:00, 14.13it/s, Loss=0.859]
+Epoch 617/10001:  60%|██████    | 6/10 [00:00<00:00, 14.13it/s, Loss=0.856]
+Epoch 617/10001:  60%|██████    | 6/10 [00:00<00:00, 14.13it/s, Loss=0.856]
+Epoch 617/10001: 100%|██████████| 10/10 [00:00<00:00, 13.50it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 618/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 618/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.851]
+Epoch 618/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.851]
+Epoch 618/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.86] 
+Epoch 618/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.852]
+Epoch 618/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.856]
+Epoch 618/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.855]
+Epoch 618/10001:  10%|█         | 1/10 [00:00<00:04,  2.20it/s, Loss=0.854]
+Epoch 618/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.854]
+Epoch 618/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.851]
+Epoch 618/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.84] 
+Epoch 618/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.849]
+Epoch 618/10001:  60%|██████    | 6/10 [00:00<00:00, 13.15it/s, Loss=0.856]
+Epoch 618/10001: 100%|██████████| 10/10 [00:00<00:00, 12.70it/s, Loss=0.856]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 619/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 619/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.853]
+Epoch 619/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.853]
+Epoch 619/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.856]
+Epoch 619/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.848]
+Epoch 619/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.85] 
+Epoch 619/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.852]
+Epoch 619/10001:  50%|█████     | 5/10 [00:00<00:00, 11.39it/s, Loss=0.852]
+Epoch 619/10001:  50%|█████     | 5/10 [00:00<00:00, 11.39it/s, Loss=0.857]
+Epoch 619/10001:  50%|█████     | 5/10 [00:00<00:00, 11.39it/s, Loss=0.851]
+Epoch 619/10001:  50%|█████     | 5/10 [00:00<00:00, 11.39it/s, Loss=0.851]
+Epoch 619/10001:  50%|█████     | 5/10 [00:00<00:00, 11.39it/s, Loss=0.849]
+Epoch 619/10001:  50%|█████     | 5/10 [00:00<00:00, 11.39it/s, Loss=0.853]
+Epoch 619/10001: 100%|██████████| 10/10 [00:00<00:00, 21.26it/s, Loss=0.853]
+Epoch 619/10001: 100%|██████████| 10/10 [00:00<00:00, 13.02it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 620/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 620/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.841]
+Epoch 620/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.841]
+Epoch 620/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.853]
+Epoch 620/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.849]
+Epoch 620/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.852]
+Epoch 620/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.852]
+Epoch 620/10001:  10%|█         | 1/10 [00:00<00:04,  2.16it/s, Loss=0.846]
+Epoch 620/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.846]
+Epoch 620/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.844]
+Epoch 620/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.848]
+Epoch 620/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.853]
+Epoch 620/10001:  60%|██████    | 6/10 [00:00<00:00, 13.18it/s, Loss=0.853]
+Epoch 620/10001: 100%|██████████| 10/10 [00:00<00:00, 13.12it/s, Loss=0.853]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 621/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 621/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 621/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.849]
+Epoch 621/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.853]
+Epoch 621/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.85] 
+Epoch 621/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.854]
+Epoch 621/10001:  10%|█         | 1/10 [00:00<00:03,  2.83it/s, Loss=0.849]
+Epoch 621/10001:  50%|█████     | 5/10 [00:00<00:00, 13.01it/s, Loss=0.849]
+Epoch 621/10001:  50%|█████     | 5/10 [00:00<00:00, 13.01it/s, Loss=0.855]
+Epoch 621/10001:  50%|█████     | 5/10 [00:00<00:00, 13.01it/s, Loss=0.853]
+Epoch 621/10001:  50%|█████     | 5/10 [00:00<00:00, 13.01it/s, Loss=0.855]
+Epoch 621/10001:  50%|█████     | 5/10 [00:00<00:00, 13.01it/s, Loss=0.851]
+Epoch 621/10001:  50%|█████     | 5/10 [00:00<00:00, 13.01it/s, Loss=0.857]
+Epoch 621/10001: 100%|██████████| 10/10 [00:00<00:00, 14.47it/s, Loss=0.857]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 622/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 622/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.849]
+Epoch 622/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.849]
+Epoch 622/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.85] 
+Epoch 622/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.859]
+Epoch 622/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.853]
+Epoch 622/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.853]
+Epoch 622/10001:  10%|█         | 1/10 [00:00<00:03,  2.41it/s, Loss=0.846]
+Epoch 622/10001:  60%|██████    | 6/10 [00:00<00:00, 13.52it/s, Loss=0.846]
+Epoch 622/10001:  60%|██████    | 6/10 [00:00<00:00, 13.52it/s, Loss=0.845]
+Epoch 622/10001:  60%|██████    | 6/10 [00:00<00:00, 13.52it/s, Loss=0.852]
+Epoch 622/10001:  60%|██████    | 6/10 [00:00<00:00, 13.52it/s, Loss=0.852]
+Epoch 622/10001:  60%|██████    | 6/10 [00:00<00:00, 13.52it/s, Loss=0.84] 
+Epoch 622/10001: 100%|██████████| 10/10 [00:00<00:00, 13.10it/s, Loss=0.84]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 623/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 623/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 623/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.85]
+Epoch 623/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.854]
+Epoch 623/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.854]
+Epoch 623/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.849]
+Epoch 623/10001:  10%|█         | 1/10 [00:00<00:03,  2.27it/s, Loss=0.854]
+Epoch 623/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.854]
+Epoch 623/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.853]
+Epoch 623/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.85] 
+Epoch 623/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.847]
+Epoch 623/10001:  50%|█████     | 5/10 [00:00<00:00, 10.91it/s, Loss=0.851]
+Epoch 623/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.59it/s, Loss=0.851]
+Epoch 623/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.59it/s, Loss=0.846]
+Epoch 623/10001: 100%|██████████| 10/10 [00:00<00:00, 12.18it/s, Loss=0.846]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 624/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 624/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.855]
+Epoch 624/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.855]
+Epoch 624/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.852]
+Epoch 624/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.853]
+Epoch 624/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.85] 
+Epoch 624/10001:  10%|█         | 1/10 [00:00<00:03,  2.36it/s, Loss=0.843]
+Epoch 624/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.843]
+Epoch 624/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.846]
+Epoch 624/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.853]
+Epoch 624/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.85] 
+Epoch 624/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.85]
+Epoch 624/10001:  50%|█████     | 5/10 [00:00<00:00, 11.60it/s, Loss=0.855]
+Epoch 624/10001: 100%|██████████| 10/10 [00:00<00:00, 12.84it/s, Loss=0.855]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 625/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 625/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.85]
+Epoch 625/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.85]
+Epoch 625/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.854]
+Epoch 625/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.854]
+Epoch 625/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.855]
+Epoch 625/10001:  10%|█         | 1/10 [00:00<00:03,  2.26it/s, Loss=0.864]
+Epoch 625/10001:  50%|█████     | 5/10 [00:00<00:00, 11.20it/s, Loss=0.864]
+Epoch 625/10001:  50%|█████     | 5/10 [00:00<00:00, 11.20it/s, Loss=0.85] 
+Epoch 625/10001:  50%|█████     | 5/10 [00:00<00:00, 11.20it/s, Loss=0.854]
+Epoch 625/10001:  50%|█████     | 5/10 [00:00<00:00, 11.20it/s, Loss=0.848]
+Epoch 625/10001:  50%|█████     | 5/10 [00:00<00:00, 11.20it/s, Loss=0.852]
+Epoch 625/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.79it/s, Loss=0.852]
+Epoch 625/10001:  90%|█████████ | 9/10 [00:00<00:00, 17.79it/s, Loss=0.847]
+Epoch 625/10001: 100%|██████████| 10/10 [00:00<00:00, 12.46it/s, Loss=0.847]
+
+  0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 626/10001:   0%|          | 0/10 [00:00<?, ?it/s]
+Epoch 626/10001:   0%|          | 0/10 [00:00<?, ?it/s, Loss=0.852]
+Epoch 626/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.852]
+Epoch 626/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.851]
+Epoch 626/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.845]
+Epoch 626/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.849]
+Epoch 626/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.85] 
+Epoch 626/10001:  10%|█         | 1/10 [00:00<00:03,  2.65it/s, Loss=0.848]
+Epoch 626/10001:  60%|██████    | 6/10 [00:00<00:00, 14.44it/s, Loss=0.848]
+Epoch 626/10001:  60%|██████    | 6/10 [00:00<00:00, 14.44it/s, Loss=0.849]
+Epoch 626/10001:  60%|██████    | 6/10 [00:00<00:00, 14.44it/s, Loss=0.843]
+Epoch 626/10001:  60%|██████    | 6/10 [00:00<00:00, 14.44it/s, Loss=0.851]
+Epoch 626/10001:  60%|██████    | 6/10 [00:00<00:00, 14.44it/s, Loss=0.846]Early stopping
+
+Epoch 626/10001: 100%|██████████| 10/10 [00:00<00:00, 13.91it/s, Loss=0.846]
+Time:  465.51175355911255
+[TabSyn] Training complete (VAE + Diffusion)
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/X_cat_test.npy b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/X_cat_test.npy
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/X_cat_train.npy b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/X_cat_train.npy
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/info.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/info.json
new file mode 100644
index 0000000000000000000000000000000000000000..5d13142a47905418a98d07a59e989becd106cf6c
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/info.json
@@ -0,0 +1,93 @@
+{
+  "name": "tabsyn_c20",
+  "task_type": "multiclass",
+  "n_num_features": 6,
+  "n_cat_features": 0,
+  "train_size": 35855,
+  "num_col_idx": [
+    0,
+    1,
+    2,
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+    5
+  ],
+  "cat_col_idx": [],
+  "target_col_idx": [
+    6
+  ],
+  "column_names": [
+    "white_piece0_strength",
+    "white_piece0_file",
+    "white_piece0_rank",
+    "black_piece0_strength",
+    "black_piece0_file",
+    "black_piece0_rank",
+    "class"
+  ],
+  "train_num": 35855,
+  "test_num": 35855,
+  "header": 0,
+  "file_type": "csv",
+  "data_path": "data/tabsyn_c20/train.csv",
+  "test_path": null,
+  "idx_mapping": {
+    "0": 0,
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+    "2": 2,
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+  },
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+    "3": "black_piece0_strength",
+    "4": "black_piece0_file",
+    "5": "black_piece0_rank",
+    "6": "class"
+  },
+  "n_classes": 3,
+  "metadata": {
+    "columns": {
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+        "sdtype": "numerical",
+        "computer_representation": "Float"
+      },
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+        "computer_representation": "Float"
+      },
+      "2": {
+        "sdtype": "numerical",
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+      },
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+        "computer_representation": "Float"
+      },
+      "6": {
+        "sdtype": "categorical"
+      }
+    }
+  }
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/test.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/test.csv
new file mode 100644
index 0000000000000000000000000000000000000000..15564e116776d6bccf27b892018adab7bb12f3b8
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/test.csv
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/train.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/train.csv
new file mode 100644
index 0000000000000000000000000000000000000000..15564e116776d6bccf27b892018adab7bb12f3b8
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/data/tabsyn_c20/train.csv
@@ -0,0 +1,35856 @@
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/normalized_schema_snapshot.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/normalized_schema_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..cec2d0784b7af841ccc2f6c9ebae396d125b6b16
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/normalized_schema_snapshot.json
@@ -0,0 +1,152 @@
+{
+  "dataset_id": "c20",
+  "target_column": "class",
+  "task_type": "classification",
+  "columns": [
+    {
+      "name": "white_piece0_strength",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.000139,
+        "example_values": [
+          "7",
+          "0",
+          "4",
+          "5",
+          "6"
+        ]
+      }
+    },
+    {
+      "name": "white_piece0_file",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7,
+        "unique_ratio": 0.000195,
+        "example_values": [
+          "5",
+          "6",
+          "3",
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "white_piece0_rank",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 9,
+        "unique_ratio": 0.000251,
+        "example_values": [
+          "8",
+          "0",
+          "1",
+          "3",
+          "7"
+        ]
+      }
+    },
+    {
+      "name": "black_piece0_strength",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.000139,
+        "example_values": [
+          "4",
+          "7",
+          "0",
+          "6",
+          "5"
+        ]
+      }
+    },
+    {
+      "name": "black_piece0_file",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7,
+        "unique_ratio": 0.000195,
+        "example_values": [
+          "1",
+          "0",
+          "3",
+          "4",
+          "6"
+        ]
+      }
+    },
+    {
+      "name": "black_piece0_rank",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 9,
+        "unique_ratio": 0.000251,
+        "example_values": [
+          "7",
+          "2",
+          "5",
+          "1",
+          "4"
+        ]
+      }
+    },
+    {
+      "name": "class",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3,
+        "unique_ratio": 8.4e-05,
+        "example_values": [
+          "w",
+          "b",
+          "d"
+        ]
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/public_gate_report.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/public_gate_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..7c6872c0280d7e7ef8d16e613861f880d01ca1ba
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/public_gate_report.json
@@ -0,0 +1,37 @@
+{
+  "dataset_id": "c20",
+  "status": "pass",
+  "checks": [
+    {
+      "check_id": "PG001_csv_parse_ok",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG002_split_header_consistent",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG003_profile_header_match",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG004_missing_token_normalized",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG005_semantic_type_validated",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG006_target_defined_and_valid",
+      "status": "pass"
+    }
+  ],
+  "target_column": "class",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-test.csv"
+  }
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/staged_input_manifest.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/staged_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..0df893985fdb9e1b688a41b03ba1fb041d9e1129
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/staged_input_manifest.json
@@ -0,0 +1,157 @@
+{
+  "dataset_id": "c20",
+  "target_column": "class",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/public_gate_report.json",
+  "column_schema": [
+    {
+      "name": "white_piece0_strength",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.000139,
+        "example_values": [
+          "7",
+          "0",
+          "4",
+          "5",
+          "6"
+        ]
+      }
+    },
+    {
+      "name": "white_piece0_file",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7,
+        "unique_ratio": 0.000195,
+        "example_values": [
+          "5",
+          "6",
+          "3",
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "white_piece0_rank",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 9,
+        "unique_ratio": 0.000251,
+        "example_values": [
+          "8",
+          "0",
+          "1",
+          "3",
+          "7"
+        ]
+      }
+    },
+    {
+      "name": "black_piece0_strength",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 5,
+        "unique_ratio": 0.000139,
+        "example_values": [
+          "4",
+          "7",
+          "0",
+          "6",
+          "5"
+        ]
+      }
+    },
+    {
+      "name": "black_piece0_file",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7,
+        "unique_ratio": 0.000195,
+        "example_values": [
+          "1",
+          "0",
+          "3",
+          "4",
+          "6"
+        ]
+      }
+    },
+    {
+      "name": "black_piece0_rank",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 9,
+        "unique_ratio": 0.000251,
+        "example_values": [
+          "7",
+          "2",
+          "5",
+          "1",
+          "4"
+        ]
+      }
+    },
+    {
+      "name": "class",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3,
+        "unique_ratio": 8.4e-05,
+        "example_values": [
+          "w",
+          "b",
+          "d"
+        ]
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/staged_features.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/staged_features.json
new file mode 100644
index 0000000000000000000000000000000000000000..7bfaf356cdd18982cf935867692dd592258079ce
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/staged_features.json
@@ -0,0 +1,37 @@
+[
+  {
+    "feature_name": "white_piece0_strength",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "white_piece0_file",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "white_piece0_rank",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "black_piece0_strength",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "black_piece0_file",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "black_piece0_rank",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "class",
+    "data_type": "categorical",
+    "is_target": true
+  }
+]
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/test.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/test.csv
new file mode 100644
index 0000000000000000000000000000000000000000..16155ab429bf343dd53395a591530f7ed75e6f3d
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/test.csv
@@ -0,0 +1,4484 @@
+white_piece0_strength,white_piece0_file,white_piece0_rank,black_piece0_strength,black_piece0_file,black_piece0_rank,class
+6,6,4,4,0,7,w
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/train.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/train.csv
new file mode 100644
index 0000000000000000000000000000000000000000..ff1d6c45adabbcfc2073a4e8ffcf5f3cb6dce40b
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/train.csv
@@ -0,0 +1,35856 @@
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/val.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/val.csv
new file mode 100644
index 0000000000000000000000000000000000000000..52fbe5eefe17f1a2eec6b31636950952bafdab26
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/val.csv
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/adapter_report.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/adapter_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..6c8cd6ee3d1ae98b8a18be98cc34203e7454528c
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/adapter_report.json
@@ -0,0 +1,7 @@
+{
+  "adapter_ready_status": "pass",
+  "adapter_fail_reason_code": null,
+  "adapter_fail_detail": null,
+  "adapter_transforms_applied": [],
+  "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/model_input_manifest.json"
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/adapter_transforms_applied.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/adapter_transforms_applied.json
new file mode 100644
index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/adapter_transforms_applied.json
@@ -0,0 +1 @@
+[]
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/model_input_manifest.json b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/model_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..b46a857a556bfec3c4dc5e293b081cad7a90d0c6
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/tabsyn/model_input_manifest.json
@@ -0,0 +1,159 @@
+{
+  "dataset_id": "c20",
+  "model": "tabsyn",
+  "target_column": "class",
+  "task_type": "classification",
+  "column_schema": [
+    {
+      "name": "white_piece0_strength",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_count": 5,
+        "unique_ratio": 0.000139,
+        "example_values": [
+          "7",
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+          "4",
+          "5",
+          "6"
+        ]
+      }
+    },
+    {
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_count": 7,
+        "unique_ratio": 0.000195,
+        "example_values": [
+          "5",
+          "6",
+          "3",
+          "0",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "white_piece0_rank",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
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+          "1",
+          "3",
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+        ]
+      }
+    },
+    {
+      "name": "black_piece0_strength",
+      "role": "feature",
+      "semantic_type": "numeric",
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+      "missing_tokens": [],
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+      "impute_strategy": "median",
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+        ]
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+    },
+    {
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+          "3",
+          "4",
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+        ]
+      }
+    },
+    {
+      "name": "black_piece0_rank",
+      "role": "feature",
+      "semantic_type": "numeric",
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+      "missing_tokens": [],
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+      "impute_strategy": "median",
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+        "example_values": [
+          "7",
+          "2",
+          "5",
+          "1",
+          "4"
+        ]
+      }
+    },
+    {
+      "name": "class",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3,
+        "unique_ratio": 8.4e-05,
+        "example_values": [
+          "w",
+          "b",
+          "d"
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/public_gate/public_gate_report.json"
+}
\ No newline at end of file
diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/synthetic/tabsyn_c20/real.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/synthetic/tabsyn_c20/real.csv
new file mode 100644
index 0000000000000000000000000000000000000000..15564e116776d6bccf27b892018adab7bb12f3b8
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/synthetic/tabsyn_c20/real.csv
@@ -0,0 +1,35856 @@
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diff --git a/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/synthetic/tabsyn_c20/test.csv b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/synthetic/tabsyn_c20/test.csv
new file mode 100644
index 0000000000000000000000000000000000000000..15564e116776d6bccf27b892018adab7bb12f3b8
--- /dev/null
+++ b/SynthesizePipeline_Archive/output-SpecializedModels/c20/tabsyn/tabsyn-c20-20260426_203054/synthetic/tabsyn_c20/test.csv
@@ -0,0 +1,35856 @@
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