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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_cpo_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_cpo_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: 0.5583 |
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- Sft Loss: 3.4705 |
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- Rewards/chosen: -3.3285 |
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- Rewards/rejected: -4.3810 |
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- Rewards/accuracies: 0.7226 |
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- Rewards/margins: 1.0525 |
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- Logps/rejected: -4.3810 |
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- Logps/chosen: -3.3285 |
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- Logits/rejected: 0.2811 |
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- Logits/chosen: 0.1563 |
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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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| 0.7019 | 0.2141 | 400 | 0.6977 | 1.4219 | -1.4375 | -1.6032 | 0.5631 | 0.1657 | -1.6032 | -1.4375 | 0.2993 | 0.2138 | |
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| 0.6225 | 0.4282 | 800 | 0.6192 | 2.0573 | -2.0770 | -2.5396 | 0.6669 | 0.4626 | -2.5396 | -2.0770 | 0.3429 | 0.2570 | |
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| 0.6242 | 0.6422 | 1200 | 0.5882 | 2.6279 | -2.4850 | -3.1039 | 0.6973 | 0.6190 | -3.1039 | -2.4850 | 0.5237 | 0.4102 | |
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| 0.5405 | 0.8563 | 1600 | 0.5781 | 2.5442 | -2.4160 | -3.0202 | 0.7092 | 0.6042 | -3.0202 | -2.4160 | 0.4122 | 0.3042 | |
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| 0.6195 | 1.0704 | 2000 | 0.5673 | 2.7121 | -2.5451 | -3.2527 | 0.7129 | 0.7076 | -3.2527 | -2.5451 | 0.4573 | 0.3371 | |
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| 0.5895 | 1.2845 | 2400 | 0.5590 | 3.0631 | -2.8962 | -3.7486 | 0.7322 | 0.8524 | -3.7486 | -2.8962 | 0.3362 | 0.2174 | |
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| 0.5512 | 1.4986 | 2800 | 0.5563 | 2.9053 | -2.7513 | -3.5751 | 0.7203 | 0.8238 | -3.5751 | -2.7513 | 0.2892 | 0.1750 | |
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| 0.5766 | 1.7127 | 3200 | 0.5520 | 2.9643 | -2.8134 | -3.6655 | 0.7263 | 0.8522 | -3.6655 | -2.8134 | 0.2677 | 0.1562 | |
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| 0.5625 | 1.9267 | 3600 | 0.5478 | 3.0563 | -2.8597 | -3.7385 | 0.7255 | 0.8788 | -3.7385 | -2.8597 | 0.3670 | 0.2441 | |
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| 0.4702 | 2.1408 | 4000 | 0.5592 | 3.5119 | -3.3071 | -4.3285 | 0.7240 | 1.0214 | -4.3285 | -3.3071 | 0.2395 | 0.1198 | |
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| 0.4882 | 2.3549 | 4400 | 0.5601 | 3.5201 | -3.3795 | -4.4355 | 0.7270 | 1.0560 | -4.4355 | -3.3795 | 0.2852 | 0.1603 | |
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| 0.4952 | 2.5690 | 4800 | 0.5580 | 3.4402 | -3.3065 | -4.3570 | 0.7233 | 1.0505 | -4.3570 | -3.3065 | 0.3210 | 0.1936 | |
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| 0.4272 | 2.7831 | 5200 | 0.5579 | 3.4523 | -3.3138 | -4.3619 | 0.7233 | 1.0481 | -4.3619 | -3.3138 | 0.3592 | 0.2281 | |
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| 0.459 | 2.9972 | 5600 | 0.5583 | 3.4705 | -3.3285 | -4.3810 | 0.7226 | 1.0525 | -4.3810 | -3.3285 | 0.2811 | 0.1563 | |
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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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