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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-0.1-1e6 |
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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/ytwqoneq) |
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# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.1-1e6 |
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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: 0.4062 |
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- Logps: -90.0446 |
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- Logits: -1.4303 |
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- Objective: 0.4077 |
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- Dpo Loss: 0.6829 |
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- Regularize: 0.4077 |
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- Ranking Simple: 0.5248 |
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- Ranking Idealized: 0.5888 |
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- Ranking Idealized Expo: 0.5103 |
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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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| 0.3854 | 0.2834 | 50 | 0.4056 | -91.4065 | -1.4801 | 0.4076 | 0.6886 | 0.4076 | 0.5124 | 0.5888 | 0.5103 | |
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| 0.3126 | 0.5668 | 100 | 0.4022 | -91.3166 | -1.4526 | 0.4009 | 0.6817 | 0.4009 | 0.5207 | 0.5888 | 0.5103 | |
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| 0.2481 | 0.8503 | 150 | 0.4118 | -93.3285 | -1.4781 | 0.4156 | 0.6853 | 0.4156 | 0.5186 | 0.5888 | 0.5103 | |
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| 0.1986 | 1.1337 | 200 | 0.4053 | -90.6332 | -1.4691 | 0.4089 | 0.6828 | 0.4089 | 0.5207 | 0.5888 | 0.5103 | |
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| 0.1805 | 1.4171 | 250 | 0.4086 | -90.2497 | -1.4648 | 0.4084 | 0.6831 | 0.4084 | 0.5248 | 0.5888 | 0.5103 | |
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| 0.1668 | 1.7005 | 300 | 0.4080 | -89.8657 | -1.4761 | 0.4114 | 0.6842 | 0.4114 | 0.5207 | 0.5888 | 0.5103 | |
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| 0.1476 | 1.9839 | 350 | 0.4086 | -89.6008 | -1.4348 | 0.4084 | 0.6835 | 0.4084 | 0.5217 | 0.5888 | 0.5103 | |
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| 0.1232 | 2.2674 | 400 | 0.4064 | -89.9367 | -1.4142 | 0.4060 | 0.6825 | 0.4060 | 0.5238 | 0.5888 | 0.5103 | |
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| 0.1085 | 2.5508 | 450 | 0.4057 | -90.6112 | -1.4381 | 0.4068 | 0.6829 | 0.4068 | 0.5238 | 0.5888 | 0.5103 | |
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| 0.099 | 2.8342 | 500 | 0.4075 | -89.7867 | -1.4538 | 0.4090 | 0.6837 | 0.4090 | 0.5248 | 0.5888 | 0.5103 | |
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| 0.0841 | 3.1176 | 550 | 0.4074 | -89.1923 | -1.4288 | 0.4091 | 0.6836 | 0.4091 | 0.5269 | 0.5888 | 0.5103 | |
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| 0.0673 | 3.4010 | 600 | 0.4056 | -89.8307 | -1.4326 | 0.4069 | 0.6824 | 0.4069 | 0.5238 | 0.5888 | 0.5103 | |
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| 0.0589 | 3.6845 | 650 | 0.4060 | -89.4758 | -1.4302 | 0.4077 | 0.6829 | 0.4077 | 0.5248 | 0.5888 | 0.5103 | |
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| 0.0551 | 3.9679 | 700 | 0.4065 | -90.0660 | -1.4301 | 0.4080 | 0.6831 | 0.4080 | 0.5238 | 0.5888 | 0.5103 | |
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| 0.042 | 4.2513 | 750 | 0.4064 | -90.0447 | -1.4307 | 0.4078 | 0.6830 | 0.4078 | 0.5248 | 0.5888 | 0.5103 | |
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| 0.0411 | 4.5347 | 800 | 0.4062 | -90.1140 | -1.4310 | 0.4078 | 0.6830 | 0.4078 | 0.5238 | 0.5888 | 0.5103 | |
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| 0.0355 | 4.8181 | 850 | 0.4062 | -90.0432 | -1.4302 | 0.4077 | 0.6829 | 0.4077 | 0.5248 | 0.5888 | 0.5103 | |
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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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