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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_magiccoder_default |
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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_magiccoder_default |
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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: 0.9894 |
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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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| 0.8215 | 0.0261 | 4 | 0.9220 | |
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| 0.9247 | 0.0522 | 8 | 0.9780 | |
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| 0.9611 | 0.0783 | 12 | 0.9693 | |
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| 0.9392 | 0.1044 | 16 | 0.9867 | |
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| 1.0135 | 0.1305 | 20 | 1.0108 | |
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| 0.9152 | 0.1566 | 24 | 1.0167 | |
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| 0.9298 | 0.1827 | 28 | 1.0251 | |
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| 1.0625 | 0.2088 | 32 | 1.0349 | |
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| 0.9695 | 0.2349 | 36 | 1.0332 | |
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| 1.0104 | 0.2610 | 40 | 1.0390 | |
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| 1.0721 | 0.2871 | 44 | 1.0406 | |
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| 1.0397 | 0.3132 | 48 | 1.0449 | |
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| 0.9623 | 0.3393 | 52 | 1.0448 | |
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| 0.9735 | 0.3654 | 56 | 1.0436 | |
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| 1.0016 | 0.3915 | 60 | 1.0431 | |
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| 1.0557 | 0.4176 | 64 | 1.0401 | |
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| 1.0377 | 0.4437 | 68 | 1.0373 | |
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| 1.0022 | 0.4698 | 72 | 1.0361 | |
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| 1.0193 | 0.4959 | 76 | 1.0328 | |
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| 0.9806 | 0.5220 | 80 | 1.0301 | |
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| 1.0542 | 0.5481 | 84 | 1.0263 | |
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| 0.9692 | 0.5742 | 88 | 1.0244 | |
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| 1.0464 | 0.6003 | 92 | 1.0215 | |
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| 0.9771 | 0.6264 | 96 | 1.0166 | |
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| 1.0659 | 0.6525 | 100 | 1.0146 | |
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| 0.9476 | 0.6786 | 104 | 1.0106 | |
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| 0.983 | 0.7047 | 108 | 1.0074 | |
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| 0.9585 | 0.7308 | 112 | 1.0035 | |
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| 0.9193 | 0.7569 | 116 | 0.9997 | |
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| 0.9041 | 0.7830 | 120 | 0.9975 | |
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| 0.9697 | 0.8091 | 124 | 0.9954 | |
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| 0.9464 | 0.8352 | 128 | 0.9933 | |
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| 1.0252 | 0.8613 | 132 | 0.9917 | |
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| 0.9665 | 0.8874 | 136 | 0.9909 | |
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| 0.9948 | 0.9135 | 140 | 0.9904 | |
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| 0.946 | 0.9396 | 144 | 0.9897 | |
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| 1.0095 | 0.9657 | 148 | 0.9896 | |
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| 0.9675 | 0.9918 | 152 | 0.9894 | |
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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 |
