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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Qwen/Qwen2-0.5B-Instruct |
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tags: |
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- trl |
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- reward-trainer |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: Qwen2-0.5B-Reward |
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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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# Qwen2-0.5B-Reward |
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This model is a fine-tuned version of [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5212 |
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- Accuracy: 0.731 |
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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: 1e-05 |
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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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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 64 |
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- total_eval_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: linear |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.6316 | 0.0516 | 50 | 0.5943 | 0.666 | |
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| 0.573 | 0.1032 | 100 | 0.5857 | 0.698 | |
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| 0.5809 | 0.1548 | 150 | 0.5718 | 0.705 | |
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| 0.5493 | 0.2064 | 200 | 0.5450 | 0.714 | |
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| 0.5649 | 0.2580 | 250 | 0.5483 | 0.713 | |
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| 0.5585 | 0.3096 | 300 | 0.5265 | 0.734 | |
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| 0.5431 | 0.3612 | 350 | 0.5295 | 0.732 | |
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| 0.5209 | 0.4128 | 400 | 0.5334 | 0.735 | |
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| 0.5414 | 0.4644 | 450 | 0.5409 | 0.726 | |
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| 0.525 | 0.5160 | 500 | 0.5387 | 0.731 | |
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| 0.5242 | 0.5676 | 550 | 0.5255 | 0.727 | |
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| 0.521 | 0.6192 | 600 | 0.5208 | 0.727 | |
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| 0.5227 | 0.6708 | 650 | 0.5191 | 0.736 | |
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| 0.5132 | 0.7224 | 700 | 0.5186 | 0.728 | |
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| 0.5145 | 0.7740 | 750 | 0.5236 | 0.729 | |
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| 0.514 | 0.8256 | 800 | 0.5249 | 0.728 | |
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| 0.5087 | 0.8772 | 850 | 0.5261 | 0.725 | |
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| 0.5009 | 0.9288 | 900 | 0.5229 | 0.727 | |
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| 0.4989 | 0.9804 | 950 | 0.5213 | 0.731 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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