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0000100_adapters.safetensors

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0000600_adapters.safetensors

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adapter_config.json

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+{
+    "adapter_path": "models/lora/mistral_lora_telegram_20251111_114741",
+    "batch_size": 2,
+    "config": null,
+    "data": "data/phase2/mlx_datasets/telegram",
+    "fine_tune_type": "lora",
+    "grad_accumulation_steps": 1,
+    "grad_checkpoint": false,
+    "iters": 600,
+    "learning_rate": 1e-05,
+    "lora_parameters": {
+        "rank": 8,
+        "dropout": 0.0,
+        "scale": 20.0
+    },
+    "lr_schedule": null,
+    "mask_prompt": false,
+    "max_seq_length": 2048,
+    "model": "models/mistral-7b-instruct-v0.3-mlx",
+    "num_layers": 16,
+    "optimizer": "adam",
+    "optimizer_config": {
+        "adam": {},
+        "adamw": {},
+        "muon": {},
+        "sgd": {},
+        "adafactor": {}
+    },
+    "project_name": null,
+    "report_to": null,
+    "resume_adapter_file": null,
+    "save_every": 100,
+    "seed": 42,
+    "steps_per_eval": 100,
+    "steps_per_report": 10,
+    "test": true,
+    "test_batches": 50,
+    "train": true,
+    "val_batches": 25
+}

adapters.safetensors

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training.log

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+Loading pretrained model
+Loading datasets
+Training
+Trainable parameters: 0.145% (10.486M/7248.024M)
+Starting training..., iters: 600
+
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+Calculating loss...: 100%|██████████| 25/25 [00:39<00:00,  1.58s/it]
+Iter 1: Val loss 2.214, Val took 39.464s
+Iter 10: Train loss 1.065, Learning Rate 1.000e-05, It/sec 0.362, Tokens/sec 431.356, Trained Tokens 11910, Peak mem 24.920 GB
+Iter 20: Train loss 0.755, Learning Rate 1.000e-05, It/sec 0.263, Tokens/sec 350.838, Trained Tokens 25233, Peak mem 37.081 GB
+Iter 30: Train loss 0.688, Learning Rate 1.000e-05, It/sec 0.352, Tokens/sec 429.868, Trained Tokens 37431, Peak mem 37.081 GB
+Iter 40: Train loss 0.557, Learning Rate 1.000e-05, It/sec 0.340, Tokens/sec 403.603, Trained Tokens 49302, Peak mem 37.081 GB
+Iter 50: Train loss 0.663, Learning Rate 1.000e-05, It/sec 0.296, Tokens/sec 387.318, Trained Tokens 62366, Peak mem 37.081 GB
+Iter 60: Train loss 0.609, Learning Rate 1.000e-05, It/sec 0.345, Tokens/sec 424.207, Trained Tokens 74645, Peak mem 37.081 GB
+Iter 70: Train loss 0.614, Learning Rate 1.000e-05, It/sec 0.344, Tokens/sec 421.161, Trained Tokens 86901, Peak mem 37.081 GB
+Iter 80: Train loss 0.607, Learning Rate 1.000e-05, It/sec 0.348, Tokens/sec 423.462, Trained Tokens 99079, Peak mem 37.081 GB
+Iter 90: Train loss 0.556, Learning Rate 1.000e-05, It/sec 0.373, Tokens/sec 439.181, Trained Tokens 110838, Peak mem 37.081 GB
+
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+Calculating loss...: 100%|██████████| 25/25 [00:40<00:00,  1.62s/it]
+Iter 100: Val loss 0.553, Val took 40.597s
+Iter 100: Train loss 0.487, Learning Rate 1.000e-05, It/sec 0.317, Tokens/sec 358.772, Trained Tokens 122142, Peak mem 37.081 GB
+Iter 100: Saved adapter weights to models/lora/mistral_lora_telegram_20251111_114741/adapters.safetensors and models/lora/mistral_lora_telegram_20251111_114741/0000100_adapters.safetensors.
+Iter 110: Train loss 0.556, Learning Rate 1.000e-05, It/sec 0.366, Tokens/sec 430.562, Trained Tokens 133896, Peak mem 37.081 GB
+Iter 120: Train loss 0.550, Learning Rate 1.000e-05, It/sec 0.348, Tokens/sec 437.090, Trained Tokens 146466, Peak mem 37.081 GB
+Iter 130: Train loss 0.499, Learning Rate 1.000e-05, It/sec 0.349, Tokens/sec 430.415, Trained Tokens 158812, Peak mem 37.081 GB
+Iter 140: Train loss 0.393, Learning Rate 1.000e-05, It/sec 0.436, Tokens/sec 465.004, Trained Tokens 169489, Peak mem 37.081 GB
+Iter 150: Train loss 0.506, Learning Rate 1.000e-05, It/sec 0.372, Tokens/sec 438.469, Trained Tokens 181272, Peak mem 37.081 GB
+Iter 160: Train loss 0.484, Learning Rate 1.000e-05, It/sec 0.375, Tokens/sec 443.286, Trained Tokens 193104, Peak mem 37.081 GB
+Iter 170: Train loss 0.480, Learning Rate 1.000e-05, It/sec 0.399, Tokens/sec 448.274, Trained Tokens 204339, Peak mem 37.081 GB
+Iter 180: Train loss 0.491, Learning Rate 1.000e-05, It/sec 0.374, Tokens/sec 442.924, Trained Tokens 216181, Peak mem 37.081 GB
+Iter 190: Train loss 0.612, Learning Rate 1.000e-05, It/sec 0.259, Tokens/sec 348.364, Trained Tokens 229607, Peak mem 37.123 GB
+
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+Calculating loss...: 100%|██████████| 25/25 [00:46<00:00,  1.87s/it]
+Iter 200: Val loss 0.499, Val took 46.784s
+Iter 200: Train loss 0.426, Learning Rate 1.000e-05, It/sec 0.364, Tokens/sec 420.021, Trained Tokens 241139, Peak mem 37.123 GB
+Iter 200: Saved adapter weights to models/lora/mistral_lora_telegram_20251111_114741/adapters.safetensors and models/lora/mistral_lora_telegram_20251111_114741/0000200_adapters.safetensors.
+Iter 210: Train loss 0.402, Learning Rate 1.000e-05, It/sec 0.364, Tokens/sec 403.442, Trained Tokens 252219, Peak mem 37.123 GB
+Iter 220: Train loss 0.432, Learning Rate 1.000e-05, It/sec 0.408, Tokens/sec 467.043, Trained Tokens 263665, Peak mem 37.123 GB
+Iter 230: Train loss 0.562, Learning Rate 1.000e-05, It/sec 0.369, Tokens/sec 447.334, Trained Tokens 275796, Peak mem 37.123 GB
+Iter 240: Train loss 0.491, Learning Rate 1.000e-05, It/sec 0.396, Tokens/sec 461.514, Trained Tokens 287447, Peak mem 37.123 GB
+Iter 250: Train loss 0.460, Learning Rate 1.000e-05, It/sec 0.391, Tokens/sec 453.744, Trained Tokens 299037, Peak mem 37.123 GB
+Iter 260: Train loss 0.462, Learning Rate 1.000e-05, It/sec 0.403, Tokens/sec 470.594, Trained Tokens 310708, Peak mem 37.123 GB
+Iter 270: Train loss 0.411, Learning Rate 1.000e-05, It/sec 0.397, Tokens/sec 455.131, Trained Tokens 322185, Peak mem 37.123 GB
+Iter 280: Train loss 0.388, Learning Rate 1.000e-05, It/sec 0.386, Tokens/sec 447.749, Trained Tokens 333784, Peak mem 37.123 GB
+Iter 290: Train loss 0.506, Learning Rate 1.000e-05, It/sec 0.401, Tokens/sec 459.746, Trained Tokens 345244, Peak mem 37.123 GB
+
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+Calculating loss...: 100%|██████████| 25/25 [00:40<00:00,  1.61s/it]
+Iter 300: Val loss 0.475, Val took 40.184s
+Iter 300: Train loss 0.520, Learning Rate 1.000e-05, It/sec 0.420, Tokens/sec 467.207, Trained Tokens 356356, Peak mem 37.123 GB
+Iter 300: Saved adapter weights to models/lora/mistral_lora_telegram_20251111_114741/adapters.safetensors and models/lora/mistral_lora_telegram_20251111_114741/0000300_adapters.safetensors.
+Iter 310: Train loss 0.429, Learning Rate 1.000e-05, It/sec 0.430, Tokens/sec 478.254, Trained Tokens 367482, Peak mem 37.123 GB
+Iter 320: Train loss 0.420, Learning Rate 1.000e-05, It/sec 0.373, Tokens/sec 439.972, Trained Tokens 379266, Peak mem 37.123 GB
+Iter 330: Train loss 0.480, Learning Rate 1.000e-05, It/sec 0.399, Tokens/sec 462.754, Trained Tokens 390875, Peak mem 37.123 GB
+Iter 340: Train loss 0.456, Learning Rate 1.000e-05, It/sec 0.404, Tokens/sec 456.805, Trained Tokens 402182, Peak mem 37.123 GB
+Iter 350: Train loss 0.639, Learning Rate 1.000e-05, It/sec 0.300, Tokens/sec 410.751, Trained Tokens 415852, Peak mem 37.972 GB
+Iter 360: Train loss 0.522, Learning Rate 1.000e-05, It/sec 0.407, Tokens/sec 474.435, Trained Tokens 427505, Peak mem 37.972 GB
+Iter 370: Train loss 0.525, Learning Rate 1.000e-05, It/sec 0.332, Tokens/sec 434.123, Trained Tokens 440587, Peak mem 37.972 GB
+Iter 380: Train loss 0.424, Learning Rate 1.000e-05, It/sec 0.374, Tokens/sec 446.958, Trained Tokens 452536, Peak mem 37.972 GB
+Iter 390: Train loss 0.428, Learning Rate 1.000e-05, It/sec 0.357, Tokens/sec 444.952, Trained Tokens 464991, Peak mem 37.972 GB
+
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+Calculating loss...: 100%|██████████| 25/25 [00:43<00:00,  1.75s/it]
+Iter 400: Val loss 0.508, Val took 43.651s
+Iter 400: Train loss 0.352, Learning Rate 1.000e-05, It/sec 0.346, Tokens/sec 403.495, Trained Tokens 476660, Peak mem 37.972 GB
+Iter 400: Saved adapter weights to models/lora/mistral_lora_telegram_20251111_114741/adapters.safetensors and models/lora/mistral_lora_telegram_20251111_114741/0000400_adapters.safetensors.
+Iter 410: Train loss 0.362, Learning Rate 1.000e-05, It/sec 0.354, Tokens/sec 436.195, Trained Tokens 488988, Peak mem 37.972 GB
+Iter 420: Train loss 0.319, Learning Rate 1.000e-05, It/sec 0.412, Tokens/sec 477.171, Trained Tokens 500576, Peak mem 37.972 GB
+Iter 430: Train loss 0.347, Learning Rate 1.000e-05, It/sec 0.394, Tokens/sec 461.272, Trained Tokens 512284, Peak mem 37.972 GB
+Iter 440: Train loss 0.370, Learning Rate 1.000e-05, It/sec 0.375, Tokens/sec 436.054, Trained Tokens 523900, Peak mem 37.972 GB
+Iter 450: Train loss 0.370, Learning Rate 1.000e-05, It/sec 0.375, Tokens/sec 460.385, Trained Tokens 536188, Peak mem 37.972 GB
+Iter 460: Train loss 0.362, Learning Rate 1.000e-05, It/sec 0.401, Tokens/sec 460.743, Trained Tokens 547689, Peak mem 37.972 GB
+Iter 470: Train loss 0.343, Learning Rate 1.000e-05, It/sec 0.391, Tokens/sec 464.058, Trained Tokens 559569, Peak mem 37.972 GB
+Iter 480: Train loss 0.375, Learning Rate 1.000e-05, It/sec 0.358, Tokens/sec 445.015, Trained Tokens 572002, Peak mem 37.972 GB
+Iter 490: Train loss 0.338, Learning Rate 1.000e-05, It/sec 0.408, Tokens/sec 471.137, Trained Tokens 583561, Peak mem 37.972 GB
+
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+Calculating loss...: 100%|██████████| 25/25 [00:37<00:00,  1.47s/it]
+Calculating loss...: 100%|██��███████| 25/25 [00:37<00:00,  1.51s/it]
+Iter 500: Val loss 0.472, Val took 37.645s
+Iter 500: Train loss 0.357, Learning Rate 1.000e-05, It/sec 0.371, Tokens/sec 445.737, Trained Tokens 595562, Peak mem 37.972 GB
+Iter 500: Saved adapter weights to models/lora/mistral_lora_telegram_20251111_114741/adapters.safetensors and models/lora/mistral_lora_telegram_20251111_114741/0000500_adapters.safetensors.
+Iter 510: Train loss 0.461, Learning Rate 1.000e-05, It/sec 0.360, Tokens/sec 451.720, Trained Tokens 608094, Peak mem 37.972 GB
+Iter 520: Train loss 0.350, Learning Rate 1.000e-05, It/sec 0.396, Tokens/sec 460.678, Trained Tokens 619734, Peak mem 37.972 GB
+Iter 530: Train loss 0.403, Learning Rate 1.000e-05, It/sec 0.380, Tokens/sec 459.285, Trained Tokens 631829, Peak mem 37.972 GB
+Iter 540: Train loss 0.311, Learning Rate 1.000e-05, It/sec 0.436, Tokens/sec 473.710, Trained Tokens 642682, Peak mem 37.972 GB
+Iter 550: Train loss 0.350, Learning Rate 1.000e-05, It/sec 0.393, Tokens/sec 459.128, Trained Tokens 654367, Peak mem 37.972 GB
+Iter 560: Train loss 0.484, Learning Rate 1.000e-05, It/sec 0.319, Tokens/sec 420.622, Trained Tokens 667572, Peak mem 37.972 GB
+Iter 570: Train loss 0.390, Learning Rate 1.000e-05, It/sec 0.394, Tokens/sec 464.738, Trained Tokens 679358, Peak mem 37.972 GB
+Iter 580: Train loss 0.364, Learning Rate 1.000e-05, It/sec 0.399, Tokens/sec 460.012, Trained Tokens 690891, Peak mem 37.972 GB
+Iter 590: Train loss 0.337, Learning Rate 1.000e-05, It/sec 0.401, Tokens/sec 468.869, Trained Tokens 702595, Peak mem 37.972 GB
+
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+Calculating loss...: 100%|██████████| 25/25 [00:36<00:00,  1.48s/it]
+Iter 600: Val loss 0.427, Val took 36.973s
+Iter 600: Train loss 0.346, Learning Rate 1.000e-05, It/sec 0.427, Tokens/sec 474.136, Trained Tokens 713698, Peak mem 37.972 GB
+Iter 600: Saved adapter weights to models/lora/mistral_lora_telegram_20251111_114741/adapters.safetensors and models/lora/mistral_lora_telegram_20251111_114741/0000600_adapters.safetensors.
+Saved final weights to models/lora/mistral_lora_telegram_20251111_114741/adapters.safetensors.
+Testing
+
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+Calculating loss...: 100%|██████████| 50/50 [01:22<00:00,  1.59s/it]
+Calculating loss...: 100%|██████████| 50/50 [01:22<00:00,  1.65s/it]
+Test loss 0.474, Test ppl 1.606.