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End of training

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README.md ADDED
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+ ---
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+ base_model: unsloth/mistral-7b-v0.3-bnb-4bit
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+ library_name: peft
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+ license: apache-2.0
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+ tags:
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+ - unsloth
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+ - generated_from_trainer
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+ model-index:
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+ - name: Mistral-7B-v0.3_metamath_default
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Mistral-7B-v0.3_metamath_default
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+
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+ This model is a fine-tuned version of [unsloth/mistral-7b-v0.3-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-v0.3-bnb-4bit) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 4.0734
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 64
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.02
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 0.7559 | 0.0211 | 13 | 8.3985 |
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+ | 9.4604 | 0.0421 | 26 | 6.8141 |
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+ | 6.7353 | 0.0632 | 39 | 6.4223 |
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+ | 6.4242 | 0.0842 | 52 | 6.2759 |
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+ | 6.1115 | 0.1053 | 65 | 6.0333 |
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+ | 5.9214 | 0.1264 | 78 | 5.8343 |
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+ | 5.6735 | 0.1474 | 91 | 5.5846 |
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+ | 5.557 | 0.1685 | 104 | 5.4916 |
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+ | 5.3297 | 0.1896 | 117 | 5.2345 |
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+ | 5.1963 | 0.2106 | 130 | 5.1310 |
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+ | 5.1252 | 0.2317 | 143 | 5.0674 |
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+ | 4.983 | 0.2527 | 156 | 4.9390 |
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+ | 4.8933 | 0.2738 | 169 | 4.8252 |
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+ | 4.7722 | 0.2949 | 182 | 4.7449 |
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+ | 4.7722 | 0.3159 | 195 | 4.7386 |
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+ | 4.6446 | 0.3370 | 208 | 4.6346 |
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+ | 4.5823 | 0.3580 | 221 | 4.5544 |
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+ | 4.576 | 0.3791 | 234 | 4.5238 |
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+ | 4.5056 | 0.4002 | 247 | 4.6538 |
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+ | 4.5501 | 0.4212 | 260 | 4.4766 |
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+ | 4.5197 | 0.4423 | 273 | 4.4369 |
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+ | 4.6259 | 0.4633 | 286 | 4.4561 |
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+ | 4.546 | 0.4844 | 299 | 4.4278 |
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+ | 4.3478 | 0.5055 | 312 | 4.3790 |
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+ | 4.3754 | 0.5265 | 325 | 4.3635 |
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+ | 4.2714 | 0.5476 | 338 | 4.3611 |
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+ | 4.3724 | 0.5687 | 351 | 4.3629 |
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+ | 4.2961 | 0.5897 | 364 | 4.2578 |
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+ | 4.2806 | 0.6108 | 377 | 4.2863 |
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+ | 4.3088 | 0.6318 | 390 | 4.2221 |
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+ | 4.2165 | 0.6529 | 403 | 4.2158 |
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+ | 4.1776 | 0.6740 | 416 | 4.1896 |
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+ | 4.2615 | 0.6950 | 429 | 4.3146 |
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+ | 4.2536 | 0.7161 | 442 | 4.2153 |
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+ | 4.1308 | 0.7371 | 455 | 4.1701 |
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+ | 4.1749 | 0.7582 | 468 | 4.1346 |
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+ | 4.1219 | 0.7793 | 481 | 4.1276 |
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+ | 4.136 | 0.8003 | 494 | 4.1162 |
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+ | 4.1453 | 0.8214 | 507 | 4.1070 |
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+ | 4.1025 | 0.8424 | 520 | 4.1167 |
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+ | 4.1207 | 0.8635 | 533 | 4.0925 |
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+ | 4.0847 | 0.8846 | 546 | 4.0926 |
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+ | 4.1504 | 0.9056 | 559 | 4.0795 |
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+ | 4.1211 | 0.9267 | 572 | 4.0711 |
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+ | 4.038 | 0.9478 | 585 | 4.0763 |
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+ | 4.0944 | 0.9688 | 598 | 4.0744 |
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+ | 4.0771 | 0.9899 | 611 | 4.0734 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.44.0
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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