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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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- alignment-handbook |
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- ndcg |
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- trl |
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- expo |
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- generated_from_trainer |
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- trl |
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- expo |
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- alignment-handbook |
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- ndcg |
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- generated_from_trainer |
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datasets: |
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- hZzy/train_pairwise |
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model-index: |
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- name: qwen2.5-0.5b-expo-DPO-ES-TRY |
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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/jz5qh3m8) |
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# qwen2.5-0.5b-expo-DPO-ES-TRY |
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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 the hZzy/train_pairwise dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6866 |
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- Logps: -91.4116 |
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- Logits: -1.5339 |
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- Objective: 0.6926 |
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- Dpo Loss: 0.6926 |
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- Regularize: 0.6926 |
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- Ranking Simple: 0.5052 |
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- Ranking Idealized: 0.5888 |
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- Ranking Idealized Expo: 0.5093 |
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- Dpo Wo Beta: -0.9551 |
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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: 5e-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 | Dpo Loss | Dpo Wo Beta | Logits | Logps | Validation Loss | Objective | Ranking Idealized | Ranking Idealized Expo | Ranking Simple | Regularize | |
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|:-------------:|:------:|:----:|:--------:|:-----------:|:-------:|:---------:|:---------------:|:---------:|:-----------------:|:----------------------:|:--------------:|:----------:| |
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| 0.672 | 0.2041 | 36 | 0.6926 | -0.9551 | -1.5339 | -91.4116 | 0.6866 | 0.6926 | 0.5888 | 0.5093 | 0.5052 | 0.6926 | |
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| 0.6533 | 0.4081 | 72 | 0.6885 | -1.1473 | -1.6311 | -92.4758 | 0.6769 | 0.6885 | 0.5888 | 0.5093 | 0.5176 | 0.6885 | |
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| 0.604 | 0.6122 | 108 | 0.6853 | -1.3961 | -1.7691 | -94.0584 | 0.6773 | 0.6853 | 0.5888 | 0.5093 | 0.5186 | 0.6853 | |
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| 0.5911 | 0.8162 | 144 | 0.6886 | -1.5153 | -1.8165 | -95.7578 | 0.6775 | 0.6886 | 0.5888 | 0.5093 | 0.5186 | 0.6886 | |
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| 0.5482 | 1.0203 | 180 | 0.6859 | -98.1346 | -1.8457 | 0.6998 | 0.6998 | 0.6998 | 0.5238 | 0.5888 | 0.5093 | -1.8685 | |
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| 0.5171 | 1.2244 | 216 | 0.6891 | -99.3936 | -1.8859 | 0.7004 | 0.7004 | 0.7004 | 0.5248 | 0.5888 | 0.5093 | -2.0594 | |
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| 0.5093 | 1.4284 | 252 | 0.6999 | -102.0847 | -1.8968 | 0.7119 | 0.7119 | 0.7119 | 0.5238 | 0.5888 | 0.5093 | -2.3165 | |
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| 0.4986 | 1.6325 | 288 | 0.6981 | -102.1441 | -1.9005 | 0.7090 | 0.7090 | 0.7090 | 0.5279 | 0.5888 | 0.5093 | -2.2741 | |
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| 0.5055 | 1.8366 | 324 | 0.6965 | -101.5796 | -1.8981 | 0.7080 | 0.7080 | 0.7080 | 0.5279 | 0.5888 | 0.5093 | -2.2649 | |
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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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