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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-0.05-1e6 |
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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/b5meuzz3) |
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# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.05-1e6 |
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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: 0.4083 |
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- Logps: -95.9768 |
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- Logits: -1.6921 |
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- Objective: 0.4121 |
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- Dpo Loss: 0.6843 |
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- Regularize: 0.4121 |
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- Ranking Simple: 0.5207 |
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- Ranking Idealized: 0.6570 |
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- Ranking Idealized Expo: 0.5114 |
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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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| 0.4009 | 0.2834 | 50 | 0.4077 | -90.3481 | -1.5066 | 0.4091 | 0.6906 | 0.4091 | 0.5145 | 0.6570 | 0.5114 | |
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| 0.3456 | 0.5668 | 100 | 0.4037 | -92.6246 | -1.6104 | 0.4081 | 0.6867 | 0.4081 | 0.5207 | 0.6570 | 0.5114 | |
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| 0.2786 | 0.8503 | 150 | 0.4061 | -94.6236 | -1.6473 | 0.4131 | 0.6873 | 0.4131 | 0.5207 | 0.6570 | 0.5114 | |
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| 0.2075 | 1.1337 | 200 | 0.4085 | -95.7674 | -1.6490 | 0.4120 | 0.6856 | 0.4120 | 0.5176 | 0.6570 | 0.5114 | |
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| 0.1852 | 1.4171 | 250 | 0.4045 | -95.1014 | -1.6977 | 0.4080 | 0.6845 | 0.4080 | 0.5227 | 0.6570 | 0.5114 | |
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| 0.172 | 1.7005 | 300 | 0.4055 | -95.9442 | -1.6403 | 0.4098 | 0.6843 | 0.4098 | 0.5227 | 0.6570 | 0.5114 | |
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| 0.1504 | 1.9839 | 350 | 0.4066 | -96.3838 | -1.6735 | 0.4094 | 0.6840 | 0.4094 | 0.5196 | 0.6570 | 0.5114 | |
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| 0.1241 | 2.2674 | 400 | 0.4076 | -95.9834 | -1.6893 | 0.4112 | 0.6844 | 0.4112 | 0.5238 | 0.6570 | 0.5114 | |
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| 0.1083 | 2.5508 | 450 | 0.4061 | -96.4275 | -1.6814 | 0.4094 | 0.6838 | 0.4094 | 0.5196 | 0.6570 | 0.5114 | |
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| 0.0989 | 2.8342 | 500 | 0.4076 | -95.7645 | -1.6797 | 0.4115 | 0.6844 | 0.4115 | 0.5176 | 0.6570 | 0.5114 | |
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| 0.0857 | 3.1176 | 550 | 0.4070 | -96.7057 | -1.6864 | 0.4108 | 0.6841 | 0.4108 | 0.5196 | 0.6570 | 0.5114 | |
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| 0.0723 | 3.4010 | 600 | 0.4083 | -96.7714 | -1.6934 | 0.4112 | 0.6840 | 0.4112 | 0.5227 | 0.6570 | 0.5114 | |
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| 0.0603 | 3.6845 | 650 | 0.4085 | -95.6858 | -1.6889 | 0.4126 | 0.6846 | 0.4126 | 0.5207 | 0.6570 | 0.5114 | |
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| 0.0658 | 3.9679 | 700 | 0.4086 | -95.9264 | -1.6962 | 0.4119 | 0.6843 | 0.4119 | 0.5217 | 0.6570 | 0.5114 | |
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| 0.0521 | 4.2513 | 750 | 0.4083 | -95.9188 | -1.6900 | 0.4119 | 0.6843 | 0.4119 | 0.5227 | 0.6570 | 0.5114 | |
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| 0.0529 | 4.5347 | 800 | 0.4081 | -95.8100 | -1.6918 | 0.4119 | 0.6843 | 0.4119 | 0.5207 | 0.6570 | 0.5114 | |
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| 0.0471 | 4.8181 | 850 | 0.4083 | -95.9782 | -1.6920 | 0.4121 | 0.6844 | 0.4121 | 0.5196 | 0.6570 | 0.5114 | |
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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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