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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-0.005-5e6 |
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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/3gvck2ki) |
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# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.005-5e6 |
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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: 0.3951 |
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- Logps: -195.4572 |
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- Logits: -3.2699 |
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- Objective: 0.3956 |
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- Dpo Loss: 0.6771 |
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- Regularize: 0.3956 |
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- Ranking Simple: 0.5661 |
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- Ranking Idealized: 0.9194 |
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- Ranking Idealized Expo: 0.5310 |
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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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| 0.4052 | 0.2834 | 50 | 0.4107 | -129.0883 | -1.8292 | 0.4120 | 0.6914 | 0.4120 | 0.5372 | 0.9194 | 0.5310 | |
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| 0.3407 | 0.5668 | 100 | 0.4017 | -173.3319 | -2.5066 | 0.4063 | 0.6839 | 0.4063 | 0.5548 | 0.9194 | 0.5310 | |
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| 0.2596 | 0.8503 | 150 | 0.4017 | -188.6395 | -2.4464 | 0.4052 | 0.6806 | 0.4052 | 0.5424 | 0.9194 | 0.5310 | |
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| 0.1965 | 1.1337 | 200 | 0.4002 | -193.1247 | -2.5977 | 0.4041 | 0.6801 | 0.4041 | 0.5589 | 0.9194 | 0.5310 | |
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| 0.1784 | 1.4171 | 250 | 0.3990 | -189.4701 | -2.7528 | 0.4023 | 0.6802 | 0.4023 | 0.5620 | 0.9194 | 0.5310 | |
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| 0.1717 | 1.7005 | 300 | 0.4021 | -195.7304 | -2.8777 | 0.4042 | 0.6799 | 0.4042 | 0.5455 | 0.9194 | 0.5310 | |
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| 0.1527 | 1.9839 | 350 | 0.3960 | -211.6068 | -3.1101 | 0.3970 | 0.6760 | 0.3970 | 0.5558 | 0.9194 | 0.5310 | |
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| 0.1267 | 2.2674 | 400 | 0.3981 | -201.0368 | -3.2515 | 0.3998 | 0.6776 | 0.3998 | 0.5620 | 0.9194 | 0.5310 | |
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| 0.1121 | 2.5508 | 450 | 0.3957 | -192.7809 | -2.9523 | 0.3976 | 0.6782 | 0.3976 | 0.5620 | 0.9194 | 0.5310 | |
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| 0.1063 | 2.8342 | 500 | 0.3941 | -195.7920 | -3.2835 | 0.3949 | 0.6760 | 0.3949 | 0.5671 | 0.9194 | 0.5310 | |
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| 0.0891 | 3.1176 | 550 | 0.3956 | -196.1659 | -3.1953 | 0.3960 | 0.6777 | 0.3960 | 0.5610 | 0.9194 | 0.5310 | |
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| 0.0749 | 3.4010 | 600 | 0.3962 | -194.1237 | -3.1966 | 0.3973 | 0.6781 | 0.3973 | 0.5744 | 0.9194 | 0.5310 | |
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| 0.062 | 3.6845 | 650 | 0.3956 | -195.3244 | -3.2412 | 0.3967 | 0.6778 | 0.3967 | 0.5702 | 0.9194 | 0.5310 | |
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| 0.0583 | 3.9679 | 700 | 0.3956 | -196.4469 | -3.2432 | 0.3961 | 0.6772 | 0.3961 | 0.5640 | 0.9194 | 0.5310 | |
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| 0.0451 | 4.2513 | 750 | 0.3952 | -195.4398 | -3.2666 | 0.3955 | 0.6771 | 0.3955 | 0.5671 | 0.9194 | 0.5310 | |
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| 0.0438 | 4.5347 | 800 | 0.3952 | -195.2319 | -3.2693 | 0.3956 | 0.6771 | 0.3956 | 0.5661 | 0.9194 | 0.5310 | |
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| 0.0408 | 4.8181 | 850 | 0.3951 | -195.5095 | -3.2704 | 0.3956 | 0.6771 | 0.3956 | 0.5661 | 0.9194 | 0.5310 | |
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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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