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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: 0.5182 |
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- Accuracy: 0.728 |
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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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| 0.6444 | 0.0516 | 50 | 0.6037 | 0.672 | |
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| 0.5825 | 0.1032 | 100 | 0.5859 | 0.682 | |
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| 0.5732 | 0.1548 | 150 | 0.5751 | 0.704 | |
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| 0.5494 | 0.2064 | 200 | 0.5514 | 0.701 | |
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| 0.5654 | 0.2580 | 250 | 0.5427 | 0.709 | |
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| 0.5514 | 0.3096 | 300 | 0.5309 | 0.723 | |
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| 0.537 | 0.3612 | 350 | 0.5259 | 0.735 | |
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| 0.5236 | 0.4128 | 400 | 0.5368 | 0.714 | |
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| 0.536 | 0.4644 | 450 | 0.5451 | 0.726 | |
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| 0.5236 | 0.5160 | 500 | 0.5371 | 0.727 | |
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| 0.526 | 0.5676 | 550 | 0.5293 | 0.729 | |
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| 0.5197 | 0.6192 | 600 | 0.5239 | 0.727 | |
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| 0.525 | 0.6708 | 650 | 0.5227 | 0.732 | |
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| 0.5123 | 0.7224 | 700 | 0.5206 | 0.723 | |
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| 0.5171 | 0.7740 | 750 | 0.5237 | 0.718 | |
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| 0.5156 | 0.8256 | 800 | 0.5245 | 0.722 | |
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| 0.5115 | 0.8772 | 850 | 0.5234 | 0.723 | |
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| 0.5007 | 0.9288 | 900 | 0.5207 | 0.729 | |
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| 0.5018 | 0.9804 | 950 | 0.5182 | 0.728 | |
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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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