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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- unsloth |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-v0.3 |
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model-index: |
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- name: mistral_7b_v_Magiccoder_evol_10k |
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results: [] |
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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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# mistral_7b_v_Magiccoder_evol_10k |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1309 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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_steps: 0.02 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.1655 | 0.0261 | 4 | 1.1621 | |
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| 1.0912 | 0.0523 | 8 | 1.1461 | |
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| 1.1696 | 0.0784 | 12 | 1.1691 | |
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| 1.0845 | 0.1046 | 16 | 1.1686 | |
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| 1.1548 | 0.1307 | 20 | 1.1627 | |
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| 1.0495 | 0.1569 | 24 | 1.1600 | |
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| 1.192 | 0.1830 | 28 | 1.1692 | |
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| 1.1397 | 0.2092 | 32 | 1.1666 | |
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| 1.0956 | 0.2353 | 36 | 1.1564 | |
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| 1.1748 | 0.2614 | 40 | 1.1647 | |
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| 1.1924 | 0.2876 | 44 | 1.1664 | |
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| 1.1258 | 0.3137 | 48 | 1.1596 | |
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| 1.1319 | 0.3399 | 52 | 1.1619 | |
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| 1.1099 | 0.3660 | 56 | 1.1577 | |
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| 1.122 | 0.3922 | 60 | 1.1573 | |
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| 1.1749 | 0.4183 | 64 | 1.1538 | |
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| 1.0708 | 0.4444 | 68 | 1.1579 | |
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| 1.0763 | 0.4706 | 72 | 1.1419 | |
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| 1.0635 | 0.4967 | 76 | 1.1494 | |
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| 1.1717 | 0.5229 | 80 | 1.1519 | |
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| 1.0674 | 0.5490 | 84 | 1.1404 | |
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| 1.1492 | 0.5752 | 88 | 1.1620 | |
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| 1.2029 | 0.6013 | 92 | 1.1477 | |
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| 1.1744 | 0.6275 | 96 | 1.1346 | |
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| 1.104 | 0.6536 | 100 | 1.1438 | |
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| 1.1398 | 0.6797 | 104 | 1.1436 | |
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| 1.1296 | 0.7059 | 108 | 1.1409 | |
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| 1.0167 | 0.7320 | 112 | 1.1469 | |
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| 1.1048 | 0.7582 | 116 | 1.1396 | |
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| 1.1004 | 0.7843 | 120 | 1.1358 | |
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| 1.1283 | 0.8105 | 124 | 1.1333 | |
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| 1.1287 | 0.8366 | 128 | 1.1322 | |
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| 1.1421 | 0.8627 | 132 | 1.1315 | |
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| 1.0848 | 0.8889 | 136 | 1.1303 | |
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| 1.184 | 0.9150 | 140 | 1.1300 | |
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| 1.0453 | 0.9412 | 144 | 1.1304 | |
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| 1.0604 | 0.9673 | 148 | 1.1307 | |
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| 1.2116 | 0.9935 | 152 | 1.1309 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
