| Loading pretrained model |
| Loading datasets |
| Training |
| Trainable parameters: 0.078% (11.469M/14770.034M) |
| Starting training..., iters: 600 |
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| Iter 1: Val loss 2.630, Val took 63.650s |
| Iter 10: Train loss 2.016, Learning Rate 1.000e-05, It/sec 0.246, Tokens/sec 239.823, Trained Tokens 9738, Peak mem 40.069 GB |
| Iter 20: Train loss 1.097, Learning Rate 1.000e-05, It/sec 0.206, Tokens/sec 223.454, Trained Tokens 20566, Peak mem 51.482 GB |
| Iter 30: Train loss 0.841, Learning Rate 1.000e-05, It/sec 0.243, Tokens/sec 243.944, Trained Tokens 30620, Peak mem 51.482 GB |
| Iter 40: Train loss 0.698, Learning Rate 1.000e-05, It/sec 0.270, Tokens/sec 260.294, Trained Tokens 40275, Peak mem 51.482 GB |
| Iter 50: Train loss 0.813, Learning Rate 1.000e-05, It/sec 0.229, Tokens/sec 246.430, Trained Tokens 51030, Peak mem 51.482 GB |
| Iter 60: Train loss 0.754, Learning Rate 1.000e-05, It/sec 0.255, Tokens/sec 254.753, Trained Tokens 61017, Peak mem 51.482 GB |
| Iter 70: Train loss 0.729, Learning Rate 1.000e-05, It/sec 0.251, Tokens/sec 250.801, Trained Tokens 71015, Peak mem 51.482 GB |
| Iter 80: Train loss 0.721, Learning Rate 1.000e-05, It/sec 0.254, Tokens/sec 254.204, Trained Tokens 81010, Peak mem 51.482 GB |
| Iter 90: Train loss 0.663, Learning Rate 1.000e-05, It/sec 0.273, Tokens/sec 262.878, Trained Tokens 90638, Peak mem 51.482 GB |
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| Iter 100: Val loss 0.655, Val took 64.142s |
| Iter 100: Train loss 0.570, Learning Rate 1.000e-05, It/sec 0.271, Tokens/sec 252.471, Trained Tokens 99944, Peak mem 51.482 GB |
| Iter 100: Saved adapter weights to models/lora/deepseek_lora_telegram_20251111_165211/adapters.safetensors and models/lora/deepseek_lora_telegram_20251111_165211/0000100_adapters.safetensors. |
| Iter 110: Train loss 0.656, Learning Rate 1.000e-05, It/sec 0.271, Tokens/sec 261.990, Trained Tokens 109594, Peak mem 51.482 GB |
| Iter 120: Train loss 0.670, Learning Rate 1.000e-05, It/sec 0.249, Tokens/sec 256.186, Trained Tokens 119873, Peak mem 51.482 GB |
| Iter 130: Train loss 0.610, Learning Rate 1.000e-05, It/sec 0.252, Tokens/sec 254.174, Trained Tokens 129955, Peak mem 51.482 GB |
| Iter 140: Train loss 0.454, Learning Rate 1.000e-05, It/sec 0.311, Tokens/sec 270.304, Trained Tokens 138638, Peak mem 51.482 GB |
| Iter 150: Train loss 0.595, Learning Rate 1.000e-05, It/sec 0.264, Tokens/sec 254.198, Trained Tokens 148254, Peak mem 51.482 GB |
| Iter 160: Train loss 0.571, Learning Rate 1.000e-05, It/sec 0.263, Tokens/sec 254.557, Trained Tokens 157921, Peak mem 51.482 GB |
| Iter 170: Train loss 0.552, Learning Rate 1.000e-05, It/sec 0.292, Tokens/sec 267.427, Trained Tokens 167073, Peak mem 51.482 GB |
| Iter 180: Train loss 0.571, Learning Rate 1.000e-05, It/sec 0.269, Tokens/sec 260.904, Trained Tokens 176788, Peak mem 51.482 GB |
| Iter 190: Train loss 0.712, Learning Rate 1.000e-05, It/sec 0.215, Tokens/sec 236.971, Trained Tokens 187826, Peak mem 52.133 GB |
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| Iter 200: Val loss 0.573, Val took 64.542s |
| Iter 200: Train loss 0.489, Learning Rate 1.000e-05, It/sec 0.281, Tokens/sec 264.627, Trained Tokens 197242, Peak mem 52.133 GB |
| Iter 200: Saved adapter weights to models/lora/deepseek_lora_telegram_20251111_165211/adapters.safetensors and models/lora/deepseek_lora_telegram_20251111_165211/0000200_adapters.safetensors. |
| Iter 210: Train loss 0.478, Learning Rate 1.000e-05, It/sec 0.295, Tokens/sec 265.899, Trained Tokens 206252, Peak mem 52.133 GB |
| Iter 220: Train loss 0.500, Learning Rate 1.000e-05, It/sec 0.288, Tokens/sec 268.788, Trained Tokens 215583, Peak mem 52.133 GB |
| Iter 230: Train loss 0.658, Learning Rate 1.000e-05, It/sec 0.258, Tokens/sec 253.876, Trained Tokens 225430, Peak mem 52.133 GB |
| Iter 240: Train loss 0.583, Learning Rate 1.000e-05, It/sec 0.277, Tokens/sec 263.746, Trained Tokens 234953, Peak mem 52.133 GB |
| Iter 250: Train loss 0.531, Learning Rate 1.000e-05, It/sec 0.273, Tokens/sec 258.514, Trained Tokens 244424, Peak mem 52.133 GB |
| Iter 260: Train loss 0.540, Learning Rate 1.000e-05, It/sec 0.275, Tokens/sec 263.070, Trained Tokens 254004, Peak mem 52.133 GB |
| Iter 270: Train loss 0.464, Learning Rate 1.000e-05, It/sec 0.275, Tokens/sec 257.103, Trained Tokens 263367, Peak mem 52.133 GB |
| Iter 280: Train loss 0.445, Learning Rate 1.000e-05, It/sec 0.269, Tokens/sec 254.944, Trained Tokens 272830, Peak mem 52.133 GB |
| Iter 290: Train loss 0.567, Learning Rate 1.000e-05, It/sec 0.272, Tokens/sec 256.184, Trained Tokens 282233, Peak mem 52.133 GB |
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| Iter 300: Val loss 0.551, Val took 64.368s |
| Iter 300: Train loss 0.578, Learning Rate 1.000e-05, It/sec 0.288, Tokens/sec 264.039, Trained Tokens 291397, Peak mem 52.133 GB |
| Iter 300: Saved adapter weights to models/lora/deepseek_lora_telegram_20251111_165211/adapters.safetensors and models/lora/deepseek_lora_telegram_20251111_165211/0000300_adapters.safetensors. |
| Iter 310: Train loss 0.490, Learning Rate 1.000e-05, It/sec 0.294, Tokens/sec 268.104, Trained Tokens 300506, Peak mem 52.133 GB |
| Iter 320: Train loss 0.494, Learning Rate 1.000e-05, It/sec 0.273, Tokens/sec 255.665, Trained Tokens 309868, Peak mem 52.133 GB |
| Iter 330: Train loss 0.553, Learning Rate 1.000e-05, It/sec 0.274, Tokens/sec 260.283, Trained Tokens 319352, Peak mem 52.133 GB |
| Iter 340: Train loss 0.510, Learning Rate 1.000e-05, It/sec 0.275, Tokens/sec 255.333, Trained Tokens 328629, Peak mem 52.133 GB |
| Iter 350: Train loss 0.754, Learning Rate 1.000e-05, It/sec 0.199, Tokens/sec 223.530, Trained Tokens 339841, Peak mem 53.360 GB |
| Iter 360: Train loss 0.582, Learning Rate 1.000e-05, It/sec 0.279, Tokens/sec 268.722, Trained Tokens 349481, Peak mem 53.360 GB |
| Iter 370: Train loss 0.637, Learning Rate 1.000e-05, It/sec 0.231, Tokens/sec 247.694, Trained Tokens 360226, Peak mem 53.360 GB |
| Iter 380: Train loss 0.558, Learning Rate 1.000e-05, It/sec 0.258, Tokens/sec 253.024, Trained Tokens 370048, Peak mem 53.360 GB |
| Iter 390: Train loss 0.568, Learning Rate 1.000e-05, It/sec 0.251, Tokens/sec 254.267, Trained Tokens 380194, Peak mem 53.360 GB |
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| Iter 400: Val loss 0.584, Val took 63.439s |
| Iter 400: Train loss 0.464, Learning Rate 1.000e-05, It/sec 0.273, Tokens/sec 261.717, Trained Tokens 389793, Peak mem 53.360 GB |
| Iter 400: Saved adapter weights to models/lora/deepseek_lora_telegram_20251111_165211/adapters.safetensors and models/lora/deepseek_lora_telegram_20251111_165211/0000400_adapters.safetensors. |
| Iter 410: Train loss 0.492, Learning Rate 1.000e-05, It/sec 0.253, Tokens/sec 255.097, Trained Tokens 399884, Peak mem 53.360 GB |
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| Iter 450: Train loss 0.497, Learning Rate 1.000e-05, It/sec 0.263, Tokens/sec 263.457, Trained Tokens 438545, Peak mem 53.360 GB |
| Iter 460: Train loss 0.485, Learning Rate 1.000e-05, It/sec 0.278, Tokens/sec 261.986, Trained Tokens 447955, Peak mem 53.360 GB |
| Iter 470: Train loss 0.471, Learning Rate 1.000e-05, It/sec 0.274, Tokens/sec 261.977, Trained Tokens 457532, Peak mem 53.360 GB |
| Iter 480: Train loss 0.498, Learning Rate 1.000e-05, It/sec 0.245, Tokens/sec 249.742, Trained Tokens 467722, Peak mem 53.360 GB |
| Iter 490: Train loss 0.471, Learning Rate 1.000e-05, It/sec 0.282, Tokens/sec 265.978, Trained Tokens 477156, Peak mem 53.360 GB |
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| Calculating loss...: 24%|βββ | 6/25 [00:13<00:44, 2.32s/it] |
| Calculating loss...: 28%|βββ | 7/25 [00:16<00:45, 2.54s/it] |
| Calculating loss...: 32%|ββββ | 8/25 [00:19<00:41, 2.42s/it] |
| Calculating loss...: 36%|ββββ | 9/25 [00:21<00:40, 2.51s/it] |
| Calculating loss...: 40%|ββββ | 10/25 [00:24<00:36, 2.45s/it] |
| Calculating loss...: 44%|βββββ | 11/25 [00:26<00:32, 2.35s/it] |
| Calculating loss...: 48%|βββββ | 12/25 [00:28<00:30, 2.34s/it] |
| Calculating loss...: 52%|ββββββ | 13/25 [00:30<00:28, 2.37s/it] |
| Calculating loss...: 56%|ββββββ | 14/25 [00:33<00:26, 2.39s/it] |
| Calculating loss...: 60%|ββββββ | 15/25 [00:37<00:29, 2.98s/it] |
| Calculating loss...: 64%|βββββββ | 16/25 [00:40<00:25, 2.81s/it] |
| Calculating loss...: 68%|βββββββ | 17/25 [00:42<00:20, 2.60s/it] |
| Calculating loss...: 72%|ββββββββ | 18/25 [00:44<00:16, 2.42s/it] |
| Calculating loss...: 76%|ββββββββ | 19/25 [00:46<00:13, 2.32s/it] |
| Calculating loss...: 80%|ββββββββ | 20/25 [00:48<00:11, 2.26s/it] |
| Calculating loss...: 84%|βββββββββ | 21/25 [00:51<00:09, 2.37s/it] |
| Calculating loss...: 88%|βββββββββ | 22/25 [00:53<00:07, 2.35s/it] |
| Calculating loss...: 92%|ββββββββββ| 23/25 [00:55<00:04, 2.27s/it] |
| Calculating loss...: 96%|ββββββββββ| 24/25 [00:57<00:02, 2.29s/it] |
| Calculating loss...: 100%|ββββββββββ| 25/25 [01:00<00:00, 2.30s/it] |
| Calculating loss...: 100%|ββββββββββ| 25/25 [01:00<00:00, 2.40s/it] |
| Iter 500: Val loss 0.516, Val took 60.113s |
| Iter 500: Train loss 0.482, Learning Rate 1.000e-05, It/sec 0.258, Tokens/sec 252.005, Trained Tokens 486939, Peak mem 53.360 GB |
| Iter 500: Saved adapter weights to models/lora/deepseek_lora_telegram_20251111_165211/adapters.safetensors and models/lora/deepseek_lora_telegram_20251111_165211/0000500_adapters.safetensors. |
| Iter 510: Train loss 0.618, Learning Rate 1.000e-05, It/sec 0.248, Tokens/sec 253.918, Trained Tokens 497197, Peak mem 53.360 GB |
| Iter 520: Train loss 0.454, Learning Rate 1.000e-05, It/sec 0.270, Tokens/sec 257.128, Trained Tokens 506732, Peak mem 53.360 GB |
| Iter 530: Train loss 0.564, Learning Rate 1.000e-05, It/sec 0.263, Tokens/sec 260.847, Trained Tokens 516645, Peak mem 53.360 GB |
| Iter 540: Train loss 0.401, Learning Rate 1.000e-05, It/sec 0.307, Tokens/sec 272.605, Trained Tokens 525534, Peak mem 53.360 GB |
| Iter 550: Train loss 0.472, Learning Rate 1.000e-05, It/sec 0.270, Tokens/sec 258.736, Trained Tokens 535129, Peak mem 53.360 GB |
| Iter 560: Train loss 0.661, Learning Rate 1.000e-05, It/sec 0.218, Tokens/sec 236.552, Trained Tokens 545967, Peak mem 53.360 GB |
| Iter 570: Train loss 0.491, Learning Rate 1.000e-05, It/sec 0.271, Tokens/sec 261.655, Trained Tokens 555617, Peak mem 53.360 GB |
| Iter 580: Train loss 0.465, Learning Rate 1.000e-05, It/sec 0.276, Tokens/sec 260.449, Trained Tokens 565065, Peak mem 53.360 GB |
| Iter 590: Train loss 0.447, Learning Rate 1.000e-05, It/sec 0.282, Tokens/sec 267.644, Trained Tokens 574556, Peak mem 53.360 GB |
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| Calculating loss...: 0%| | 0/25 [00:00<?, ?it/s] |
| Calculating loss...: 4%|β | 1/25 [00:02<01:11, 2.97s/it] |
| Calculating loss...: 8%|β | 2/25 [00:05<00:57, 2.48s/it] |
| Calculating loss...: 12%|ββ | 3/25 [00:07<00:51, 2.32s/it] |
| Calculating loss...: 16%|ββ | 4/25 [00:09<00:48, 2.31s/it] |
| Calculating loss...: 20%|ββ | 5/25 [00:12<00:48, 2.42s/it] |
| Calculating loss...: 24%|βββ | 6/25 [00:14<00:45, 2.38s/it] |
| Calculating loss...: 28%|βββ | 7/25 [00:16<00:41, 2.29s/it] |
| Calculating loss...: 32%|ββββ | 8/25 [00:18<00:39, 2.34s/it] |
| Calculating loss...: 36%|ββββ | 9/25 [00:21<00:40, 2.51s/it] |
| Calculating loss...: 40%|ββββ | 10/25 [00:24<00:39, 2.62s/it] |
| Calculating loss...: 44%|βββββ | 11/25 [00:28<00:40, 2.88s/it] |
| Calculating loss...: 48%|βββββ | 12/25 [00:30<00:35, 2.70s/it] |
| Calculating loss...: 52%|ββββββ | 13/25 [00:32<00:30, 2.52s/it] |
| Calculating loss...: 56%|ββββββ | 14/25 [00:34<00:26, 2.40s/it] |
| Calculating loss...: 60%|ββββββ | 15/25 [00:36<00:23, 2.32s/it] |
| Calculating loss...: 64%|βββββββ | 16/25 [00:38<00:20, 2.22s/it] |
| Calculating loss...: 68%|βββββββ | 17/25 [00:40<00:17, 2.16s/it] |
| Calculating loss...: 72%|ββββββββ | 18/25 [00:43<00:15, 2.20s/it] |
| Calculating loss...: 76%|ββββββββ | 19/25 [00:45<00:12, 2.14s/it] |
| Calculating loss...: 80%|ββββββββ | 20/25 [00:47<00:10, 2.13s/it] |
| Calculating loss...: 84%|βββββββββ | 21/25 [00:49<00:08, 2.18s/it] |
| Calculating loss...: 88%|βββββββββ | 22/25 [00:51<00:06, 2.13s/it] |
| Calculating loss...: 92%|ββββββββββ| 23/25 [00:54<00:04, 2.28s/it] |
| Calculating loss...: 96%|ββββββββββ| 24/25 [00:56<00:02, 2.32s/it] |
| Calculating loss...: 100%|ββββββββββ| 25/25 [00:58<00:00, 2.27s/it] |
| Calculating loss...: 100%|ββββββββββ| 25/25 [00:58<00:00, 2.35s/it] |
| Iter 600: Val loss 0.463, Val took 58.782s |
| Iter 600: Train loss 0.456, Learning Rate 1.000e-05, It/sec 0.292, Tokens/sec 265.446, Trained Tokens 583661, Peak mem 53.360 GB |
| Iter 600: Saved adapter weights to models/lora/deepseek_lora_telegram_20251111_165211/adapters.safetensors and models/lora/deepseek_lora_telegram_20251111_165211/0000600_adapters.safetensors. |
| Saved final weights to models/lora/deepseek_lora_telegram_20251111_165211/adapters.safetensors. |
| Testing |
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| Calculating loss...: 0%| | 0/50 [00:00<?, ?it/s] |
| Calculating loss...: 2%|β | 1/50 [00:02<01:58, 2.41s/it] |
| Calculating loss...: 4%|β | 2/50 [00:04<01:47, 2.24s/it] |
| Calculating loss...: 6%|β | 3/50 [00:07<01:59, 2.54s/it] |
| Calculating loss...: 8%|β | 4/50 [00:09<01:54, 2.50s/it] |
| Calculating loss...: 10%|β | 5/50 [00:12<01:51, 2.47s/it] |
| Calculating loss...: 12%|ββ | 6/50 [00:14<01:45, 2.41s/it] |
| Calculating loss...: 14%|ββ | 7/50 [00:16<01:41, 2.37s/it] |
| Calculating loss...: 16%|ββ | 8/50 [00:18<01:35, 2.26s/it] |
| Calculating loss...: 18%|ββ | 9/50 [00:20<01:29, 2.19s/it] |
| Calculating loss...: 20%|ββ | 10/50 [00:23<01:36, 2.41s/it] |
| Calculating loss...: 22%|βββ | 11/50 [00:26<01:32, 2.37s/it] |
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| Calculating loss...: 26%|βββ | 13/50 [00:30<01:22, 2.23s/it] |
| Calculating loss...: 28%|βββ | 14/50 [00:32<01:20, 2.25s/it] |
| Calculating loss...: 30%|βββ | 15/50 [00:34<01:16, 2.18s/it] |
| Calculating loss...: 32%|ββββ | 16/50 [00:37<01:18, 2.31s/it] |
| Calculating loss...: 34%|ββββ | 17/50 [00:39<01:20, 2.44s/it] |
| Calculating loss...: 36%|ββββ | 18/50 [00:42<01:18, 2.44s/it] |
| Calculating loss...: 38%|ββββ | 19/50 [00:44<01:12, 2.34s/it] |
| Calculating loss...: 40%|ββββ | 20/50 [00:46<01:08, 2.28s/it] |
| Calculating loss...: 42%|βββββ | 21/50 [00:49<01:09, 2.38s/it] |
| Calculating loss...: 44%|βββββ | 22/50 [00:51<01:05, 2.35s/it] |
| Calculating loss...: 46%|βββββ | 23/50 [00:53<01:01, 2.29s/it] |
| Calculating loss...: 48%|βββββ | 24/50 [00:55<00:58, 2.23s/it] |
| Calculating loss...: 50%|βββββ | 25/50 [00:58<00:58, 2.35s/it] |
| Calculating loss...: 52%|ββββββ | 26/50 [01:00<00:54, 2.26s/it] |
| Calculating loss...: 54%|ββββββ | 27/50 [01:02<00:50, 2.21s/it] |
| Calculating loss...: 56%|ββββββ | 28/50 [01:04<00:48, 2.19s/it] |
| Calculating loss...: 58%|ββββββ | 29/50 [01:06<00:45, 2.17s/it] |
| Calculating loss...: 60%|ββββββ | 30/50 [01:09<00:45, 2.25s/it] |
| Calculating loss...: 62%|βββββββ | 31/50 [01:11<00:41, 2.21s/it] |
| Calculating loss...: 64%|βββββββ | 32/50 [01:14<00:43, 2.41s/it] |
| Calculating loss...: 66%|βββββββ | 33/50 [01:16<00:41, 2.42s/it] |
| Calculating loss...: 68%|βββββββ | 34/50 [01:19<00:38, 2.42s/it] |
| Calculating loss...: 70%|βββββββ | 35/50 [01:23<00:43, 2.92s/it] |
| Calculating loss...: 72%|ββββββββ | 36/50 [01:25<00:37, 2.68s/it] |
| Calculating loss...: 74%|ββββββββ | 37/50 [01:28<00:35, 2.74s/it] |
| Calculating loss...: 76%|ββββββββ | 38/50 [01:30<00:32, 2.70s/it] |
| Calculating loss...: 78%|ββββββββ | 39/50 [01:33<00:28, 2.58s/it] |
| Calculating loss...: 80%|ββββββββ | 40/50 [01:37<00:31, 3.15s/it] |
| Calculating loss...: 82%|βββββββββ | 41/50 [01:39<00:25, 2.84s/it] |
| Calculating loss...: 84%|βββββββββ | 42/50 [01:42<00:22, 2.80s/it] |
| Calculating loss...: 86%|βββββββββ | 43/50 [01:45<00:19, 2.78s/it] |
| Calculating loss...: 88%|βββββββββ | 44/50 [01:48<00:17, 2.84s/it] |
| Calculating loss...: 90%|βββββββββ | 45/50 [01:50<00:14, 2.85s/it] |
| Calculating loss...: 92%|ββββββββββ| 46/50 [01:53<00:10, 2.69s/it] |
| Calculating loss...: 94%|ββββββββββ| 47/50 [01:55<00:07, 2.57s/it] |
| Calculating loss...: 96%|ββββββββββ| 48/50 [01:57<00:04, 2.50s/it] |
| Calculating loss...: 98%|ββββββββββ| 49/50 [02:00<00:02, 2.44s/it] |
| Calculating loss...: 100%|ββββββββββ| 50/50 [02:02<00:00, 2.54s/it] |
| Calculating loss...: 100%|ββββββββββ| 50/50 [02:02<00:00, 2.46s/it] |
| Test loss 0.526, Test ppl 1.693. |
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