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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_unl_entropy_0_0 |
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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_unl_entropy_0_0 |
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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: 1.6479 |
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- Rewards/chosen: -1.3032 |
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- Rewards/rejected: -1.4993 |
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- Rewards/accuracies: 0.5712 |
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- Rewards/margins: 0.1961 |
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- Logps/rejected: -1.4993 |
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- Logps/chosen: -1.3032 |
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- Logits/rejected: 0.1464 |
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- Logits/chosen: 0.0748 |
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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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| 1.6555 | 0.2141 | 400 | 1.6941 | -1.3383 | -1.4640 | 0.5556 | 0.1257 | -1.4640 | -1.3383 | 0.4030 | 0.3137 | |
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| 1.6693 | 0.4282 | 800 | 1.6719 | -1.3149 | -1.4532 | 0.5579 | 0.1383 | -1.4532 | -1.3149 | 0.3441 | 0.2642 | |
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| 1.6204 | 0.6422 | 1200 | 1.6640 | -1.3085 | -1.4525 | 0.5556 | 0.1440 | -1.4525 | -1.3085 | 0.3559 | 0.2746 | |
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| 1.6569 | 0.8563 | 1600 | 1.6598 | -1.3094 | -1.4585 | 0.5593 | 0.1491 | -1.4585 | -1.3094 | 0.2618 | 0.1878 | |
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| 1.7111 | 1.0704 | 2000 | 1.6548 | -1.3002 | -1.4570 | 0.5653 | 0.1568 | -1.4570 | -1.3002 | 0.2290 | 0.1561 | |
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| 1.6123 | 1.2845 | 2400 | 1.6522 | -1.3029 | -1.4741 | 0.5675 | 0.1711 | -1.4741 | -1.3029 | 0.2729 | 0.1950 | |
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| 1.6687 | 1.4986 | 2800 | 1.6488 | -1.3000 | -1.4737 | 0.5697 | 0.1738 | -1.4737 | -1.3000 | 0.1754 | 0.1051 | |
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| 1.6012 | 1.7127 | 3200 | 1.6494 | -1.3010 | -1.4718 | 0.5675 | 0.1708 | -1.4718 | -1.3010 | 0.1848 | 0.1133 | |
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| 1.5646 | 1.9267 | 3600 | 1.6479 | -1.2987 | -1.4776 | 0.5682 | 0.1789 | -1.4776 | -1.2987 | 0.1466 | 0.0770 | |
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| 1.5351 | 2.1408 | 4000 | 1.6470 | -1.3020 | -1.4960 | 0.5697 | 0.1940 | -1.4960 | -1.3020 | 0.1418 | 0.0714 | |
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| 1.5309 | 2.3549 | 4400 | 1.6467 | -1.3051 | -1.5042 | 0.5727 | 0.1991 | -1.5042 | -1.3051 | 0.1132 | 0.0439 | |
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| 1.5444 | 2.5690 | 4800 | 1.6473 | -1.3034 | -1.5014 | 0.5720 | 0.1979 | -1.5014 | -1.3034 | 0.1403 | 0.0690 | |
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| 1.5671 | 2.7831 | 5200 | 1.6474 | -1.3030 | -1.4996 | 0.5705 | 0.1966 | -1.4996 | -1.3030 | 0.2002 | 0.1244 | |
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| 1.5485 | 2.9972 | 5600 | 1.6479 | -1.3031 | -1.4993 | 0.5712 | 0.1961 | -1.4993 | -1.3031 | 0.1464 | 0.0748 | |
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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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