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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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+ - trl
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+ - expo
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+ - generated_from_trainer
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+ model-index:
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+ - name: qwen2.5-0.5b-expo-DPO-EXPERIMENT
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+ results: []
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+ ---
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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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+
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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/g2cz8uwi)
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+ # qwen2.5-0.5b-expo-DPO-EXPERIMENT
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+
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6818
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+ - Logps: -92.0550
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+ - Logits: -1.5636
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+ - Objective: 0.6891
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+ - Dpo Loss: 0.6891
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+ - Regularize: 0.6891
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+ - Ranking Simple: 0.5196
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+ - Ranking Idealized: 0.5888
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+ - Ranking Idealized Expo: 0.5103
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-07
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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: 2
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+
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+ ### Training results
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+
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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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+ | 0.6855 | 0.2834 | 50 | 0.6889 | -90.7669 | -1.4343 | 0.6918 | 0.6918 | 0.6918 | 0.5103 | 0.5888 | 0.5103 |
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+ | 0.6746 | 0.5668 | 100 | 0.6858 | -90.9748 | -1.4764 | 0.6899 | 0.6899 | 0.6899 | 0.5093 | 0.5888 | 0.5103 |
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+ | 0.6601 | 0.8503 | 150 | 0.6828 | -90.8063 | -1.5179 | 0.6886 | 0.6886 | 0.6886 | 0.5134 | 0.5888 | 0.5103 |
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+ | 0.6473 | 1.1337 | 200 | 0.6826 | -91.9779 | -1.5427 | 0.6890 | 0.6890 | 0.6890 | 0.5176 | 0.5888 | 0.5103 |
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+ | 0.6449 | 1.4171 | 250 | 0.6813 | -91.6044 | -1.5537 | 0.6887 | 0.6887 | 0.6887 | 0.5176 | 0.5888 | 0.5103 |
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+ | 0.6384 | 1.7005 | 300 | 0.6818 | -92.0140 | -1.5627 | 0.6890 | 0.6890 | 0.6890 | 0.5186 | 0.5888 | 0.5103 |
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+ | 0.6431 | 1.9839 | 350 | 0.6818 | -92.0550 | -1.5636 | 0.6891 | 0.6891 | 0.6891 | 0.5196 | 0.5888 | 0.5103 |
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+
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+
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+ ### Framework versions
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+
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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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