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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_uncCPO_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_uncCPO_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: 0.0500 |
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- Sft Loss: 3.9220 |
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- Rewards/chosen: -4.3252 |
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- Rewards/rejected: -5.1044 |
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- Rewards/accuracies: 0.6892 |
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- Rewards/margins: 0.7793 |
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- Logps/rejected: -5.1044 |
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- Logps/chosen: -4.3252 |
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- Logits/rejected: 0.1444 |
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- Logits/chosen: 0.0509 |
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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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| 0.0563 | 0.2141 | 400 | 0.0573 | 4.8352 | -5.7454 | -6.0246 | 0.5445 | 0.2792 | -6.0246 | -5.7454 | 0.6512 | 0.5372 | |
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| 0.0533 | 0.4282 | 800 | 0.0524 | 4.2340 | -4.6954 | -5.0777 | 0.6157 | 0.3823 | -5.0777 | -4.6954 | 0.2939 | 0.1644 | |
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| 0.0533 | 0.6422 | 1200 | 0.0518 | 4.1504 | -4.5198 | -5.0186 | 0.6484 | 0.4989 | -5.0186 | -4.5198 | 0.4014 | 0.2684 | |
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| 0.0508 | 0.8563 | 1600 | 0.0512 | 4.0690 | -4.5220 | -5.0081 | 0.6491 | 0.4862 | -5.0081 | -4.5220 | 0.2498 | 0.1344 | |
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| 0.0529 | 1.0704 | 2000 | 0.0508 | 3.9195 | -4.3917 | -4.9646 | 0.6521 | 0.5729 | -4.9646 | -4.3917 | 0.3268 | 0.2181 | |
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| 0.0522 | 1.2845 | 2400 | 0.0504 | 4.1797 | -4.6133 | -5.2771 | 0.6647 | 0.6638 | -5.2771 | -4.6133 | 0.2727 | 0.1622 | |
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| 0.0515 | 1.4986 | 2800 | 0.0504 | 4.0933 | -4.4442 | -5.0786 | 0.6825 | 0.6344 | -5.0786 | -4.4442 | 0.2050 | 0.0984 | |
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| 0.0526 | 1.7127 | 3200 | 0.0503 | 4.0886 | -4.4943 | -5.1537 | 0.6751 | 0.6594 | -5.1537 | -4.4943 | 0.2002 | 0.0920 | |
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| 0.0533 | 1.9267 | 3600 | 0.0501 | 3.9857 | -4.3809 | -5.1003 | 0.6825 | 0.7195 | -5.1003 | -4.3809 | 0.1348 | 0.0421 | |
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| 0.0493 | 2.1408 | 4000 | 0.0500 | 3.9751 | -4.3954 | -5.1537 | 0.6840 | 0.7583 | -5.1537 | -4.3954 | 0.3029 | 0.1980 | |
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| 0.0522 | 2.3549 | 4400 | 0.0500 | 3.9820 | -4.4013 | -5.1632 | 0.6869 | 0.7619 | -5.1632 | -4.4013 | 0.2139 | 0.1131 | |
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| 0.0513 | 2.5690 | 4800 | 0.0500 | 3.9732 | -4.3709 | -5.1160 | 0.6944 | 0.7451 | -5.1160 | -4.3709 | 0.1787 | 0.0785 | |
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| 0.0498 | 2.7831 | 5200 | 0.0500 | 3.9372 | -4.3318 | -5.0969 | 0.6892 | 0.7651 | -5.0969 | -4.3318 | 0.2138 | 0.1134 | |
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| 0.0496 | 2.9972 | 5600 | 0.0500 | 3.9220 | -4.3252 | -5.1044 | 0.6892 | 0.7793 | -5.1044 | -4.3252 | 0.1444 | 0.0509 | |
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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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