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--- |
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library_name: transformers |
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license: other |
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base_model: Qwen/Qwen2.5-3B-Instruct |
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tags: |
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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: web_policy_sft |
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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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# web_policy_sft |
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This model is a fine-tuned version of [/data/hzy/models--Qwen--Qwen2.5-3B-Instruct/snapshots/aa8e72537993ba99e69dfaafa59ed015b17504d1](https://huggingface.co//data/hzy/models--Qwen--Qwen2.5-3B-Instruct/snapshots/aa8e72537993ba99e69dfaafa59ed015b17504d1) on the web_policy_sft dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1625 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 2 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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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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| 0.5121 | 0.0470 | 50 | 0.4876 | |
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| 0.4615 | 0.0940 | 100 | 0.3849 | |
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| 0.37 | 0.1409 | 150 | 0.3281 | |
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| 0.3749 | 0.1879 | 200 | 0.2892 | |
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| 0.2863 | 0.2349 | 250 | 0.2757 | |
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| 0.3078 | 0.2819 | 300 | 0.2549 | |
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| 0.2921 | 0.3289 | 350 | 0.2316 | |
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| 0.3191 | 0.3759 | 400 | 0.2353 | |
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| 0.313 | 0.4228 | 450 | 0.2231 | |
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| 0.2037 | 0.4698 | 500 | 0.2138 | |
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| 0.1729 | 0.5168 | 550 | 0.2074 | |
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| 0.289 | 0.5638 | 600 | 0.1954 | |
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| 0.2775 | 0.6108 | 650 | 0.1897 | |
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| 0.1546 | 0.6577 | 700 | 0.1814 | |
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| 0.1613 | 0.7047 | 750 | 0.1746 | |
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| 0.0956 | 0.7517 | 800 | 0.1725 | |
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| 0.1692 | 0.7987 | 850 | 0.1683 | |
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| 0.1885 | 0.8457 | 900 | 0.1653 | |
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| 0.2799 | 0.8926 | 950 | 0.1637 | |
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| 0.1971 | 0.9396 | 1000 | 0.1628 | |
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| 0.1464 | 0.9866 | 1050 | 0.1626 | |
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### Framework versions |
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- Transformers 4.57.1 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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