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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-L2EXPO-EXPERIMENT-0.5-5e6 |
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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/e9puntse) |
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# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.5-5e6 |
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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: 2.2556 |
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- Logps: -80.0690 |
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- Logits: -0.6172 |
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- Objective: 2.2419 |
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- Dpo Loss: 1.3282 |
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- Regularize: 2.2419 |
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- Ranking Simple: 0.5134 |
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- Ranking Idealized: 0.5248 |
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- Ranking Idealized Expo: 0.5093 |
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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: 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: 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 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:| |
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| 0.8081 | 0.2834 | 50 | 0.6652 | -91.9364 | -1.3308 | 0.6722 | 0.7266 | 0.6722 | 0.5124 | 0.5248 | 0.5093 | |
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| 1.4482 | 0.5668 | 100 | 1.4160 | -83.3251 | -1.0880 | 1.3662 | 0.9745 | 1.3662 | 0.5093 | 0.5248 | 0.5093 | |
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| 1.5063 | 0.8503 | 150 | 1.8403 | -79.4245 | -0.9764 | 1.8307 | 1.1388 | 1.8307 | 0.5155 | 0.5248 | 0.5093 | |
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| 1.3427 | 1.1337 | 200 | 1.9411 | -78.0898 | -0.8446 | 1.9042 | 1.1943 | 1.9042 | 0.5124 | 0.5248 | 0.5093 | |
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| 1.2385 | 1.4171 | 250 | 2.1004 | -81.0783 | -0.8252 | 2.0780 | 1.2812 | 2.0780 | 0.5072 | 0.5248 | 0.5093 | |
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| 1.1013 | 1.7005 | 300 | 2.1954 | -78.5161 | -0.6190 | 2.2003 | 1.3091 | 2.2003 | 0.5124 | 0.5248 | 0.5093 | |
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| 0.9795 | 1.9839 | 350 | 2.2001 | -78.2914 | -0.6908 | 2.1850 | 1.2866 | 2.1850 | 0.5093 | 0.5248 | 0.5093 | |
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| 0.8853 | 2.2674 | 400 | 2.2679 | -78.5732 | -0.6216 | 2.2619 | 1.3223 | 2.2619 | 0.5134 | 0.5248 | 0.5093 | |
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| 0.7605 | 2.5508 | 450 | 2.2655 | -78.2840 | -0.6826 | 2.2744 | 1.3572 | 2.2744 | 0.5145 | 0.5248 | 0.5093 | |
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| 0.6709 | 2.8342 | 500 | 2.2688 | -79.7185 | -0.6486 | 2.2578 | 1.3375 | 2.2578 | 0.5186 | 0.5248 | 0.5093 | |
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| 0.5302 | 3.1176 | 550 | 2.2598 | -80.1419 | -0.6267 | 2.2430 | 1.3210 | 2.2430 | 0.5196 | 0.5248 | 0.5093 | |
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| 0.4552 | 3.4010 | 600 | 2.2547 | -79.9582 | -0.6007 | 2.2379 | 1.3298 | 2.2379 | 0.5124 | 0.5248 | 0.5093 | |
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| 0.3981 | 3.6845 | 650 | 2.2549 | -80.1880 | -0.5995 | 2.2397 | 1.3238 | 2.2397 | 0.5155 | 0.5248 | 0.5093 | |
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| 0.3178 | 3.9679 | 700 | 2.2616 | -80.4560 | -0.6215 | 2.2539 | 1.3332 | 2.2539 | 0.5134 | 0.5248 | 0.5093 | |
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| 0.2213 | 4.2513 | 750 | 2.2620 | -80.1501 | -0.6154 | 2.2499 | 1.3297 | 2.2499 | 0.5134 | 0.5248 | 0.5093 | |
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| 0.2032 | 4.5347 | 800 | 2.2583 | -80.1241 | -0.6175 | 2.2455 | 1.3295 | 2.2455 | 0.5134 | 0.5248 | 0.5093 | |
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| 0.1935 | 4.8181 | 850 | 2.2561 | -80.0661 | -0.6169 | 2.2424 | 1.3284 | 2.2424 | 0.5134 | 0.5248 | 0.5093 | |
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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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