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--- |
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license: apache-2.0 |
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base_model: hZzy/qwen2.5-0.5b-sft-news-IFT |
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tags: |
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- trl |
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- expo |
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- generated_from_trainer |
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model-index: |
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- name: qwen2.5-0.5b-expo-DPO-EXPERIMENT |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhiyuzha-university-of-florida/huggingface/runs/g2cz8uwi) |
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# qwen2.5-0.5b-expo-DPO-EXPERIMENT |
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This model is a fine-tuned version of [hZzy/qwen2.5-0.5b-sft-news-IFT](https://huggingface.co/hZzy/qwen2.5-0.5b-sft-news-IFT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6818 |
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- Logps: -92.0550 |
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- Logits: -1.5636 |
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- Objective: 0.6891 |
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- Dpo Loss: 0.6891 |
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- Regularize: 0.6891 |
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- Ranking Simple: 0.5196 |
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- Ranking Idealized: 0.5888 |
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- Ranking Idealized Expo: 0.5103 |
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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-07 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 6 |
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- gradient_accumulation_steps: 12 |
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- total_train_batch_size: 288 |
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- total_eval_batch_size: 24 |
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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: 0.1 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Logps | Logits | Objective | Dpo Loss | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:| |
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| 0.6855 | 0.2834 | 50 | 0.6889 | -90.7669 | -1.4343 | 0.6918 | 0.6918 | 0.6918 | 0.5103 | 0.5888 | 0.5103 | |
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| 0.6746 | 0.5668 | 100 | 0.6858 | -90.9748 | -1.4764 | 0.6899 | 0.6899 | 0.6899 | 0.5093 | 0.5888 | 0.5103 | |
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| 0.6601 | 0.8503 | 150 | 0.6828 | -90.8063 | -1.5179 | 0.6886 | 0.6886 | 0.6886 | 0.5134 | 0.5888 | 0.5103 | |
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| 0.6473 | 1.1337 | 200 | 0.6826 | -91.9779 | -1.5427 | 0.6890 | 0.6890 | 0.6890 | 0.5176 | 0.5888 | 0.5103 | |
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| 0.6449 | 1.4171 | 250 | 0.6813 | -91.6044 | -1.5537 | 0.6887 | 0.6887 | 0.6887 | 0.5176 | 0.5888 | 0.5103 | |
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| 0.6384 | 1.7005 | 300 | 0.6818 | -92.0140 | -1.5627 | 0.6890 | 0.6890 | 0.6890 | 0.5186 | 0.5888 | 0.5103 | |
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| 0.6431 | 1.9839 | 350 | 0.6818 | -92.0550 | -1.5636 | 0.6891 | 0.6891 | 0.6891 | 0.5196 | 0.5888 | 0.5103 | |
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### Framework versions |
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- Transformers 4.42.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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