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--- |
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base_model: mistralai/Mistral-7B-v0.3 |
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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_pct_default_r32 |
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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-v0.3_pct_default_r32 |
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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: 2.0448 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.9915 | 0.0206 | 8 | 2.0385 | |
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| 2.054 | 0.0413 | 16 | 2.0376 | |
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| 2.0356 | 0.0619 | 24 | 2.0604 | |
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| 2.0385 | 0.0825 | 32 | 2.0639 | |
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| 2.1223 | 0.1032 | 40 | 2.0833 | |
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| 2.0677 | 0.1238 | 48 | 2.0910 | |
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| 2.0729 | 0.1444 | 56 | 2.0872 | |
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| 2.1197 | 0.1651 | 64 | 2.0973 | |
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| 2.1053 | 0.1857 | 72 | 2.0919 | |
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| 2.0848 | 0.2063 | 80 | 2.1035 | |
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| 2.1015 | 0.2270 | 88 | 2.1114 | |
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| 2.0872 | 0.2476 | 96 | 2.1133 | |
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| 2.0948 | 0.2682 | 104 | 2.1221 | |
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| 2.097 | 0.2889 | 112 | 2.1219 | |
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| 2.147 | 0.3095 | 120 | 2.1240 | |
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| 2.1315 | 0.3301 | 128 | 2.1189 | |
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| 2.1563 | 0.3508 | 136 | 2.1368 | |
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| 2.1836 | 0.3714 | 144 | 2.1271 | |
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| 2.1245 | 0.3920 | 152 | 2.1198 | |
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| 2.0947 | 0.4127 | 160 | 2.1240 | |
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| 2.1472 | 0.4333 | 168 | 2.1354 | |
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| 2.1348 | 0.4539 | 176 | 2.1261 | |
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| 2.1099 | 0.4746 | 184 | 2.1275 | |
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| 2.1006 | 0.4952 | 192 | 2.1196 | |
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| 2.1339 | 0.5158 | 200 | 2.1170 | |
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| 2.0841 | 0.5364 | 208 | 2.1105 | |
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| 2.1344 | 0.5571 | 216 | 2.1079 | |
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| 2.0732 | 0.5777 | 224 | 2.1043 | |
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| 2.0417 | 0.5983 | 232 | 2.1035 | |
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| 2.1003 | 0.6190 | 240 | 2.0967 | |
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| 2.0501 | 0.6396 | 248 | 2.1007 | |
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| 2.078 | 0.6602 | 256 | 2.0862 | |
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| 2.0507 | 0.6809 | 264 | 2.0840 | |
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| 2.0235 | 0.7015 | 272 | 2.0762 | |
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| 2.0743 | 0.7221 | 280 | 2.0723 | |
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| 2.1028 | 0.7428 | 288 | 2.0721 | |
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| 2.0987 | 0.7634 | 296 | 2.0662 | |
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| 2.0985 | 0.7840 | 304 | 2.0663 | |
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| 2.0548 | 0.8047 | 312 | 2.0602 | |
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| 2.0365 | 0.8253 | 320 | 2.0563 | |
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| 2.0102 | 0.8459 | 328 | 2.0564 | |
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| 2.0497 | 0.8666 | 336 | 2.0522 | |
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| 2.0721 | 0.8872 | 344 | 2.0471 | |
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| 2.0812 | 0.9078 | 352 | 2.0468 | |
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| 2.0475 | 0.9285 | 360 | 2.0462 | |
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| 2.0687 | 0.9491 | 368 | 2.0452 | |
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| 2.065 | 0.9697 | 376 | 2.0450 | |
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| 1.991 | 0.9904 | 384 | 2.0448 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
