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--- |
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base_model: unsloth/Qwen2-7B |
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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: Qwen2-7B_pct_reverse |
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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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# Qwen2-7B_pct_reverse |
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This model is a fine-tuned version of [unsloth/Qwen2-7B](https://huggingface.co/unsloth/Qwen2-7B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0219 |
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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: 0.0003 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.1146 | 0.0206 | 8 | 2.0126 | |
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| 2.1241 | 0.0412 | 16 | 2.0399 | |
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| 2.1297 | 0.0618 | 24 | 2.0522 | |
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| 2.0751 | 0.0824 | 32 | 2.0553 | |
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| 2.1182 | 0.1031 | 40 | 2.0606 | |
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| 2.1169 | 0.1237 | 48 | 2.0666 | |
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| 2.1253 | 0.1443 | 56 | 2.0730 | |
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| 2.1136 | 0.1649 | 64 | 2.0714 | |
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| 2.127 | 0.1855 | 72 | 2.0839 | |
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| 2.1835 | 0.2061 | 80 | 2.0803 | |
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| 2.1556 | 0.2267 | 88 | 2.0903 | |
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| 2.1396 | 0.2473 | 96 | 2.0887 | |
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| 2.1656 | 0.2680 | 104 | 2.0928 | |
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| 2.0821 | 0.2886 | 112 | 2.0880 | |
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| 2.1287 | 0.3092 | 120 | 2.0923 | |
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| 2.1298 | 0.3298 | 128 | 2.0969 | |
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| 2.1317 | 0.3504 | 136 | 2.0961 | |
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| 2.1325 | 0.3710 | 144 | 2.0906 | |
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| 2.1398 | 0.3916 | 152 | 2.0906 | |
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| 2.1569 | 0.4122 | 160 | 2.0886 | |
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| 2.195 | 0.4329 | 168 | 2.0862 | |
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| 2.1038 | 0.4535 | 176 | 2.0899 | |
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| 2.1159 | 0.4741 | 184 | 2.0845 | |
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| 2.1605 | 0.4947 | 192 | 2.0805 | |
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| 2.0894 | 0.5153 | 200 | 2.0765 | |
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| 2.1368 | 0.5359 | 208 | 2.0748 | |
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| 2.1626 | 0.5565 | 216 | 2.0715 | |
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| 2.0765 | 0.5771 | 224 | 2.0630 | |
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| 2.0879 | 0.5977 | 232 | 2.0677 | |
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| 2.0851 | 0.6184 | 240 | 2.0554 | |
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| 2.0731 | 0.6390 | 248 | 2.0549 | |
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| 2.113 | 0.6596 | 256 | 2.0517 | |
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| 2.0796 | 0.6802 | 264 | 2.0484 | |
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| 2.1406 | 0.7008 | 272 | 2.0457 | |
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| 2.0454 | 0.7214 | 280 | 2.0421 | |
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| 2.1278 | 0.7420 | 288 | 2.0378 | |
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| 2.0616 | 0.7626 | 296 | 2.0353 | |
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| 2.0697 | 0.7833 | 304 | 2.0340 | |
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| 2.0557 | 0.8039 | 312 | 2.0300 | |
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| 2.0954 | 0.8245 | 320 | 2.0304 | |
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| 2.094 | 0.8451 | 328 | 2.0297 | |
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| 2.0539 | 0.8657 | 336 | 2.0266 | |
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| 2.0866 | 0.8863 | 344 | 2.0250 | |
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| 2.061 | 0.9069 | 352 | 2.0227 | |
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| 2.126 | 0.9275 | 360 | 2.0220 | |
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| 2.0616 | 0.9481 | 368 | 2.0222 | |
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| 2.106 | 0.9688 | 376 | 2.0219 | |
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| 2.0596 | 0.9894 | 384 | 2.0219 | |
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### Framework versions |
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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 |
