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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 |
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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 |
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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: -1.3864 |
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- Rewards/accuracies: 0.5475 |
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- Rewards/margins: 0.1242 |
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- Logps/rejected: -1.3864 |
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- Logps/chosen: -1.2622 |
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- Logits/rejected: 0.1431 |
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- Logits/chosen: 0.0760 |
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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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| 1.2903 | 0.2141 | 400 | 1.3234 | -1.3231 | -1.4418 | 0.5556 | 0.1187 | -1.4418 | -1.3231 | 0.3478 | 0.2657 | |
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| 1.2586 | 0.4282 | 800 | 1.2926 | -1.2924 | -1.4167 | 0.5482 | 0.1243 | -1.4167 | -1.2924 | 0.3140 | 0.2391 | |
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| 1.217 | 0.6422 | 1200 | 1.2836 | -1.2833 | -1.4047 | 0.5475 | 0.1213 | -1.4047 | -1.2833 | 0.2906 | 0.2178 | |
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| 1.299 | 0.8563 | 1600 | 1.2774 | -1.2772 | -1.3985 | 0.5467 | 0.1213 | -1.3985 | -1.2772 | 0.2371 | 0.1683 | |
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| 1.2617 | 1.0704 | 2000 | 1.2726 | -1.2724 | -1.3958 | 0.5482 | 0.1234 | -1.3958 | -1.2724 | 0.1842 | 0.1180 | |
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| 1.1894 | 1.2845 | 2400 | 1.2689 | -1.2687 | -1.3924 | 0.5460 | 0.1238 | -1.3924 | -1.2687 | 0.1212 | 0.0586 | |
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| 1.2779 | 1.4986 | 2800 | 1.2662 | -1.2659 | -1.3880 | 0.5453 | 0.1221 | -1.3880 | -1.2659 | 0.1199 | 0.0573 | |
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| 1.225 | 1.7127 | 3200 | 1.2650 | -1.2647 | -1.3872 | 0.5490 | 0.1225 | -1.3872 | -1.2647 | 0.1854 | 0.1171 | |
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| 1.1621 | 1.9267 | 3600 | 1.2636 | -1.2634 | -1.3853 | 0.5475 | 0.1219 | -1.3853 | -1.2634 | 0.1551 | 0.0880 | |
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| 1.1565 | 2.1408 | 4000 | 1.2633 | -1.2631 | -1.3880 | 0.5482 | 0.1250 | -1.3880 | -1.2631 | 0.0952 | 0.0325 | |
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| 1.1515 | 2.3549 | 4400 | 1.2629 | -1.2626 | -1.3868 | 0.5467 | 0.1242 | -1.3868 | -1.2626 | 0.0880 | 0.0251 | |
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| 1.1364 | 2.5690 | 4800 | 1.2625 | -1.2623 | -1.3865 | 0.5467 | 0.1242 | -1.3865 | -1.2623 | 0.1292 | 0.0630 | |
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| 1.1256 | 2.7831 | 5200 | 1.2626 | -1.2623 | -1.3864 | 0.5475 | 0.1241 | -1.3864 | -1.2623 | 0.1208 | 0.0553 | |
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| 1.1655 | 2.9972 | 5600 | 1.2625 | -1.2622 | -1.3864 | 0.5475 | 0.1242 | -1.3864 | -1.2622 | 0.1431 | 0.0760 | |
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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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