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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-0.5-1e6 |
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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/fbqhf9yl) |
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# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.5-1e6 |
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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: 0.7095 |
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- Logps: -87.7114 |
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- Logits: -1.2689 |
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- Objective: 0.7117 |
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- Dpo Loss: 0.7514 |
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- Regularize: 0.7117 |
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- Ranking Simple: 0.5124 |
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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: 1e-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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| 0.3563 | 0.2834 | 50 | 0.4211 | -92.3339 | -1.4209 | 0.4280 | 0.6873 | 0.4280 | 0.5114 | 0.5248 | 0.5093 | |
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| 0.4749 | 0.5668 | 100 | 0.4673 | -91.3111 | -1.3982 | 0.4712 | 0.6958 | 0.4712 | 0.5145 | 0.5248 | 0.5093 | |
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| 0.5468 | 0.8503 | 150 | 0.5596 | -91.0759 | -1.3204 | 0.5683 | 0.7061 | 0.5683 | 0.5145 | 0.5248 | 0.5093 | |
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| 0.5501 | 1.1337 | 200 | 0.6048 | -89.7055 | -1.3004 | 0.5995 | 0.7155 | 0.5995 | 0.5062 | 0.5248 | 0.5093 | |
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| 0.5045 | 1.4171 | 250 | 0.6191 | -88.7256 | -1.3194 | 0.6397 | 0.7337 | 0.6397 | 0.5176 | 0.5248 | 0.5093 | |
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| 0.5191 | 1.7005 | 300 | 0.6502 | -87.6189 | -1.3167 | 0.6544 | 0.7342 | 0.6544 | 0.5165 | 0.5248 | 0.5093 | |
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| 0.4473 | 1.9839 | 350 | 0.6869 | -88.6205 | -1.3002 | 0.6878 | 0.7476 | 0.6878 | 0.5093 | 0.5248 | 0.5093 | |
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| 0.3926 | 2.2674 | 400 | 0.7087 | -87.7933 | -1.2740 | 0.7147 | 0.7519 | 0.7147 | 0.5114 | 0.5248 | 0.5093 | |
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| 0.3583 | 2.5508 | 450 | 0.6997 | -87.7180 | -1.2638 | 0.7073 | 0.7468 | 0.7073 | 0.5093 | 0.5248 | 0.5093 | |
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| 0.2969 | 2.8342 | 500 | 0.7206 | -87.5993 | -1.2820 | 0.7300 | 0.7570 | 0.7300 | 0.5134 | 0.5248 | 0.5093 | |
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| 0.2456 | 3.1176 | 550 | 0.7082 | -87.4857 | -1.2747 | 0.7095 | 0.7502 | 0.7095 | 0.5134 | 0.5248 | 0.5093 | |
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| 0.2121 | 3.4010 | 600 | 0.7150 | -87.8251 | -1.2611 | 0.7195 | 0.7513 | 0.7195 | 0.5124 | 0.5248 | 0.5093 | |
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| 0.1721 | 3.6845 | 650 | 0.7181 | -87.5542 | -1.2667 | 0.7210 | 0.7529 | 0.7210 | 0.5124 | 0.5248 | 0.5093 | |
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| 0.1386 | 3.9679 | 700 | 0.7065 | -87.5438 | -1.2654 | 0.7094 | 0.7514 | 0.7094 | 0.5114 | 0.5248 | 0.5093 | |
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| 0.0985 | 4.2513 | 750 | 0.7096 | -87.6431 | -1.2699 | 0.7118 | 0.7509 | 0.7118 | 0.5145 | 0.5248 | 0.5093 | |
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| 0.0882 | 4.5347 | 800 | 0.7119 | -87.7428 | -1.2693 | 0.7145 | 0.7520 | 0.7145 | 0.5114 | 0.5248 | 0.5093 | |
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| 0.0796 | 4.8181 | 850 | 0.7095 | -87.7155 | -1.2689 | 0.7118 | 0.7515 | 0.7118 | 0.5124 | 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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