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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_0_01 |
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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_0_01 |
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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: 0.6685 |
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- Sft Loss: 1.5897 |
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- Rewards/chosen: -1.6017 |
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- Rewards/rejected: -2.2330 |
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- Rewards/accuracies: 0.6506 |
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- Rewards/margins: 0.6314 |
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- Logps/rejected: -2.2330 |
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- Logps/chosen: -1.6017 |
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- Logits/rejected: 0.2142 |
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- Logits/chosen: 0.1178 |
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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 | Sft 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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| 0.6889 | 0.2141 | 400 | 0.7003 | 1.4382 | -1.5229 | -1.6955 | 0.5579 | 0.1726 | -1.6955 | -1.5229 | 0.2817 | 0.1945 | |
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| 0.6916 | 0.4282 | 800 | 0.6822 | 1.5282 | -1.5414 | -1.8469 | 0.6076 | 0.3055 | -1.8469 | -1.5414 | 0.2875 | 0.2001 | |
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| 0.6757 | 0.6422 | 1200 | 0.6771 | 1.5574 | -1.5600 | -1.9539 | 0.6217 | 0.3939 | -1.9539 | -1.5600 | 0.2922 | 0.2043 | |
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| 0.6744 | 0.8563 | 1600 | 0.6739 | 1.5959 | -1.6093 | -2.0408 | 0.6335 | 0.4315 | -2.0408 | -1.6093 | 0.2827 | 0.1913 | |
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| 0.714 | 1.0704 | 2000 | 0.6719 | 1.5564 | -1.5625 | -2.0466 | 0.6269 | 0.4841 | -2.0466 | -1.5625 | 0.1990 | 0.1104 | |
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| 0.6715 | 1.2845 | 2400 | 0.6719 | 1.5799 | -1.5845 | -2.1083 | 0.6380 | 0.5238 | -2.1083 | -1.5845 | 0.2487 | 0.1536 | |
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| 0.6658 | 1.4986 | 2800 | 0.6707 | 1.6055 | -1.6197 | -2.1818 | 0.6454 | 0.5621 | -2.1818 | -1.6197 | 0.1108 | 0.0257 | |
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| 0.6709 | 1.7127 | 3200 | 0.6701 | 1.5845 | -1.5941 | -2.1721 | 0.6476 | 0.5780 | -2.1721 | -1.5941 | 0.1373 | 0.0502 | |
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| 0.659 | 1.9267 | 3600 | 0.6686 | 1.5568 | -1.5549 | -2.1383 | 0.6454 | 0.5835 | -2.1383 | -1.5549 | 0.1189 | 0.0332 | |
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| 0.6241 | 2.1408 | 4000 | 0.6689 | 1.5859 | -1.5837 | -2.1770 | 0.6454 | 0.5933 | -2.1770 | -1.5837 | 0.1840 | 0.0917 | |
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| 0.6443 | 2.3549 | 4400 | 0.6692 | 1.5919 | -1.6001 | -2.2168 | 0.6461 | 0.6166 | -2.2168 | -1.6001 | 0.0426 | -0.0398 | |
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| 0.6356 | 2.5690 | 4800 | 0.6686 | 1.5864 | -1.5964 | -2.2216 | 0.6484 | 0.6252 | -2.2216 | -1.5964 | 0.1106 | 0.0226 | |
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| 0.6448 | 2.7831 | 5200 | 0.6683 | 1.5882 | -1.5994 | -2.2308 | 0.6506 | 0.6314 | -2.2308 | -1.5994 | 0.0974 | 0.0105 | |
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| 0.6368 | 2.9972 | 5600 | 0.6685 | 1.5897 | -1.6017 | -2.2330 | 0.6506 | 0.6314 | -2.2330 | -1.6017 | 0.2142 | 0.1178 | |
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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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