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--- |
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library_name: transformers |
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license: other |
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base_model: trl-lib/qwen1.5-0.5b-sft |
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tags: |
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- alignment-handbook |
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- trl |
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- simpo |
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- generated_from_trainer |
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- trl |
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- simpo |
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- generated_from_trainer |
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datasets: |
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- yakazimir/ultrafeedback_binarized |
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model-index: |
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- name: qwen_qfUNL_entropy |
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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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# qwen_qfUNL_entropy |
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This model is a fine-tuned version of [trl-lib/qwen1.5-0.5b-sft](https://huggingface.co/trl-lib/qwen1.5-0.5b-sft) on the yakazimir/ultrafeedback_binarized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6510 |
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- Rewards/chosen: -1.7989 |
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- Rewards/rejected: -2.5830 |
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- Rewards/accuracies: 0.6736 |
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- Rewards/margins: 0.7841 |
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- Logps/rejected: -2.5830 |
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- Logps/chosen: -1.7989 |
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- Logits/rejected: 0.0192 |
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- Logits/chosen: -0.0604 |
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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: 2 |
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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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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 32 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.6781 | 0.2141 | 400 | 0.6873 | -1.6444 | -1.8233 | 0.5475 | 0.1789 | -1.8233 | -1.6444 | 0.2857 | 0.1996 | |
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| 0.6757 | 0.4282 | 800 | 0.6641 | -1.6348 | -1.9815 | 0.6239 | 0.3467 | -1.9815 | -1.6348 | 0.3665 | 0.2730 | |
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| 0.6569 | 0.6422 | 1200 | 0.6602 | -1.7060 | -2.1644 | 0.6424 | 0.4584 | -2.1644 | -1.7060 | 0.2601 | 0.1749 | |
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| 0.6562 | 0.8563 | 1600 | 0.6584 | -1.8368 | -2.3836 | 0.6513 | 0.5468 | -2.3836 | -1.8368 | 0.1796 | 0.0944 | |
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| 0.6883 | 1.0704 | 2000 | 0.6545 | -1.7098 | -2.2986 | 0.6639 | 0.5888 | -2.2986 | -1.7098 | 0.2146 | 0.1248 | |
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| 0.6581 | 1.2845 | 2400 | 0.6533 | -1.7444 | -2.3861 | 0.6691 | 0.6417 | -2.3861 | -1.7444 | 0.1530 | 0.0644 | |
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| 0.6444 | 1.4986 | 2800 | 0.6537 | -1.7815 | -2.4833 | 0.6684 | 0.7018 | -2.4833 | -1.7815 | 0.0665 | -0.0145 | |
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| 0.6575 | 1.7127 | 3200 | 0.6520 | -1.7922 | -2.5114 | 0.6654 | 0.7192 | -2.5114 | -1.7922 | 0.1107 | 0.0260 | |
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| 0.6481 | 1.9267 | 3600 | 0.6507 | -1.7358 | -2.4632 | 0.6736 | 0.7275 | -2.4632 | -1.7358 | 0.0939 | 0.0113 | |
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| 0.607 | 2.1408 | 4000 | 0.6506 | -1.7686 | -2.5161 | 0.6751 | 0.7475 | -2.5161 | -1.7686 | 0.0842 | 0.0005 | |
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| 0.6294 | 2.3549 | 4400 | 0.6514 | -1.8215 | -2.5986 | 0.6714 | 0.7771 | -2.5986 | -1.8215 | 0.0008 | -0.0778 | |
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| 0.6098 | 2.5690 | 4800 | 0.6507 | -1.7918 | -2.5693 | 0.6766 | 0.7775 | -2.5693 | -1.7918 | 0.0735 | -0.0103 | |
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| 0.6302 | 2.7831 | 5200 | 0.6507 | -1.7943 | -2.5780 | 0.6751 | 0.7837 | -2.5780 | -1.7943 | 0.0395 | -0.0418 | |
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| 0.6181 | 2.9972 | 5600 | 0.6510 | -1.7989 | -2.5830 | 0.6736 | 0.7841 | -2.5830 | -1.7989 | 0.0192 | -0.0604 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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