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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_ce_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_ce_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: 1.2625 |
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- Rewards/chosen: -1.2622 |
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- Rewards/rejected: -1.3865 |
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- Rewards/accuracies: 0.5467 |
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- Rewards/margins: 0.1243 |
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- Logps/rejected: -1.3865 |
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- Logps/chosen: -1.2622 |
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- Logits/rejected: 0.0855 |
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- Logits/chosen: 0.0231 |
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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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| 1.2909 | 0.2141 | 400 | 1.3232 | -1.3229 | -1.4423 | 0.5549 | 0.1194 | -1.4423 | -1.3229 | 0.3582 | 0.2751 | |
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| 1.2587 | 0.4282 | 800 | 1.2927 | -1.2925 | -1.4166 | 0.5504 | 0.1242 | -1.4166 | -1.2925 | 0.3302 | 0.2542 | |
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| 1.2174 | 0.6422 | 1200 | 1.2838 | -1.2835 | -1.4045 | 0.5490 | 0.1210 | -1.4045 | -1.2835 | 0.2712 | 0.2000 | |
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| 1.2991 | 0.8563 | 1600 | 1.2773 | -1.2770 | -1.3983 | 0.5467 | 0.1213 | -1.3983 | -1.2770 | 0.2519 | 0.1821 | |
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| 1.2615 | 1.0704 | 2000 | 1.2727 | -1.2724 | -1.3955 | 0.5490 | 0.1231 | -1.3955 | -1.2724 | 0.1950 | 0.1280 | |
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| 1.1889 | 1.2845 | 2400 | 1.2689 | -1.2686 | -1.3926 | 0.5475 | 0.1239 | -1.3926 | -1.2686 | 0.1649 | 0.0990 | |
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| 1.2782 | 1.4986 | 2800 | 1.2663 | -1.2660 | -1.3882 | 0.5482 | 0.1222 | -1.3882 | -1.2660 | 0.1472 | 0.0825 | |
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| 1.225 | 1.7127 | 3200 | 1.2649 | -1.2646 | -1.3872 | 0.5460 | 0.1226 | -1.3872 | -1.2646 | 0.1561 | 0.0901 | |
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| 1.1621 | 1.9267 | 3600 | 1.2636 | -1.2633 | -1.3851 | 0.5475 | 0.1218 | -1.3851 | -1.2633 | 0.1670 | 0.0991 | |
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| 1.1574 | 2.1408 | 4000 | 1.2633 | -1.2630 | -1.3882 | 0.5467 | 0.1252 | -1.3882 | -1.2630 | 0.1189 | 0.0543 | |
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| 1.1513 | 2.3549 | 4400 | 1.2630 | -1.2627 | -1.3868 | 0.5453 | 0.1241 | -1.3868 | -1.2627 | 0.1222 | 0.0567 | |
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| 1.1366 | 2.5690 | 4800 | 1.2624 | -1.2622 | -1.3866 | 0.5475 | 0.1244 | -1.3866 | -1.2622 | 0.1424 | 0.0753 | |
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| 1.1253 | 2.7831 | 5200 | 1.2627 | -1.2624 | -1.3865 | 0.5475 | 0.1241 | -1.3865 | -1.2624 | 0.1178 | 0.0528 | |
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| 1.1657 | 2.9972 | 5600 | 1.2625 | -1.2622 | -1.3865 | 0.5467 | 0.1243 | -1.3865 | -1.2622 | 0.0855 | 0.0231 | |
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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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