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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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- 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-100 |
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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/tkmcvc2n) |
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# qwen2.5-0.5b-expo-DPO-ES-100 |
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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: 226.3468 |
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- Logps: -80.2667 |
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- Logits: -0.6269 |
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- Objective: 213.3031 |
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- Dpo Loss: 213.3031 |
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- Regularize: 213.3031 |
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- Ranking Simple: 0.5399 |
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- Ranking Idealized: 0.5212 |
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- Ranking Idealized Expo: 0.5212 |
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- Wo Beta: 6.6215 |
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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-06 |
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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: 3 |
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- gradient_accumulation_steps: 12 |
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- total_train_batch_size: 144 |
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- total_eval_batch_size: 12 |
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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: 5 |
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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 | Wo Beta | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:| |
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| 17.3723 | 0.1417 | 50 | 32.1125 | -90.9520 | -1.4391 | 31.4854 | 31.4854 | 31.4854 | 0.5264 | 0.5212 | 0.5212 | 7.6851 | |
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| 60.4454 | 0.2834 | 100 | 70.9968 | -86.6000 | -1.4386 | 70.7719 | 70.7719 | 70.7719 | 0.5305 | 0.5212 | 0.5212 | 7.5289 | |
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| 100.2237 | 0.4251 | 150 | 129.8928 | -85.7303 | -1.2892 | 126.8845 | 126.8845 | 126.8845 | 0.5321 | 0.5212 | 0.5212 | 7.4641 | |
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| 120.8284 | 0.5668 | 200 | 164.0152 | -75.5542 | -1.3195 | 159.5013 | 159.5013 | 159.5013 | 0.5357 | 0.5212 | 0.5212 | 7.1836 | |
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| 134.8217 | 0.7085 | 250 | 195.7212 | -79.3891 | -1.2058 | 190.8510 | 190.8510 | 190.8510 | 0.5285 | 0.5212 | 0.5212 | 7.2711 | |
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| 119.0273 | 0.8503 | 300 | 192.5231 | -84.2971 | -0.9945 | 188.0580 | 188.0580 | 188.0580 | 0.5357 | 0.5212 | 0.5212 | 6.9382 | |
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| 114.0792 | 0.9920 | 350 | 205.7797 | -82.1125 | -1.0045 | 192.3920 | 192.3920 | 192.3920 | 0.5409 | 0.5212 | 0.5212 | 6.9235 | |
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| 72.4145 | 1.1337 | 400 | 212.6613 | -82.8156 | -0.7120 | 204.8122 | 204.8122 | 204.8122 | 0.5409 | 0.5212 | 0.5212 | 7.0485 | |
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| 76.9668 | 1.2754 | 450 | 210.2291 | -82.4190 | -0.7807 | 203.0261 | 203.0261 | 203.0261 | 0.5383 | 0.5212 | 0.5212 | 6.9244 | |
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| 77.9261 | 1.4171 | 500 | 211.3156 | -81.3728 | -0.7438 | 202.1569 | 202.1569 | 202.1569 | 0.5362 | 0.5212 | 0.5212 | 6.8863 | |
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| 70.5755 | 1.5588 | 550 | 212.6468 | -82.3296 | -0.6838 | 200.1410 | 200.1410 | 200.1410 | 0.5430 | 0.5212 | 0.5212 | 6.7241 | |
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| 69.6026 | 1.7005 | 600 | 212.0254 | -80.7129 | -0.5569 | 196.9669 | 196.9669 | 196.9669 | 0.5419 | 0.5212 | 0.5212 | 6.6975 | |
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| 69.7829 | 1.8422 | 650 | 222.2766 | -79.4968 | -0.7062 | 209.6782 | 209.6782 | 209.6782 | 0.5404 | 0.5212 | 0.5212 | 6.6541 | |
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| 62.7864 | 1.9839 | 700 | 226.3468 | -80.2667 | -0.6269 | 213.3031 | 213.3031 | 213.3031 | 0.5399 | 0.5212 | 0.5212 | 6.6215 | |
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| 37.3326 | 2.1256 | 750 | 219.7785 | -80.5665 | -0.7007 | 208.8723 | 208.8723 | 208.8723 | 0.5440 | 0.5212 | 0.5212 | 6.7265 | |
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| 33.2099 | 2.2674 | 800 | 221.8786 | -81.8901 | -0.5673 | 207.6881 | 207.6881 | 207.6881 | 0.5450 | 0.5212 | 0.5212 | 6.6717 | |
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| 33.915 | 2.4091 | 850 | 217.6955 | -81.9134 | -0.5178 | 205.0515 | 205.0515 | 205.0515 | 0.5424 | 0.5212 | 0.5212 | 6.7249 | |
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| 35.3572 | 2.5508 | 900 | 224.5402 | -81.5880 | -0.4729 | 214.5052 | 214.5052 | 214.5052 | 0.5435 | 0.5212 | 0.5212 | 6.8278 | |
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| 31.032 | 2.6925 | 950 | 225.2907 | -80.3480 | -0.5542 | 216.5803 | 216.5803 | 216.5803 | 0.5419 | 0.5212 | 0.5212 | 6.8429 | |
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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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