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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_orpo_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_orpo_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: 0.5257 |
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- Rewards/chosen: -5.2305 |
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- Rewards/rejected: -6.3460 |
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- Rewards/accuracies: 0.7285 |
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- Rewards/margins: 1.1155 |
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- Logps/rejected: -6.3460 |
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- Logps/chosen: -5.2305 |
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- Logits/rejected: 0.3311 |
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- Logits/chosen: 0.2347 |
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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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| 0.7057 | 0.2141 | 400 | 0.7062 | -1.5154 | -1.6776 | 0.5571 | 0.1622 | -1.6776 | -1.5154 | 0.3357 | 0.2498 | |
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| 0.597 | 0.4282 | 800 | 0.5956 | -2.3371 | -2.7822 | 0.6669 | 0.4451 | -2.7822 | -2.3371 | 0.4528 | 0.3584 | |
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| 0.5883 | 0.6422 | 1200 | 0.5486 | -3.5511 | -4.2123 | 0.7211 | 0.6612 | -4.2123 | -3.5511 | 0.3923 | 0.2876 | |
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| 0.4794 | 0.8563 | 1600 | 0.5320 | -3.5255 | -4.2178 | 0.7277 | 0.6924 | -4.2178 | -3.5255 | 0.3881 | 0.2849 | |
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| 0.5765 | 1.0704 | 2000 | 0.5305 | -3.6701 | -4.4352 | 0.7240 | 0.7651 | -4.4352 | -3.6701 | 0.3104 | 0.1978 | |
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| 0.5449 | 1.2845 | 2400 | 0.5198 | -4.3149 | -5.2348 | 0.7352 | 0.9199 | -5.2348 | -4.3149 | 0.2247 | 0.1184 | |
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| 0.518 | 1.4986 | 2800 | 0.5189 | -4.2439 | -5.1423 | 0.7352 | 0.8983 | -5.1423 | -4.2439 | 0.3318 | 0.2186 | |
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| 0.5602 | 1.7127 | 3200 | 0.5174 | -4.3315 | -5.2509 | 0.7381 | 0.9194 | -5.2509 | -4.3315 | 0.3472 | 0.2362 | |
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| 0.5482 | 1.9267 | 3600 | 0.5152 | -4.3680 | -5.3320 | 0.7329 | 0.9640 | -5.3320 | -4.3680 | 0.3330 | 0.2233 | |
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| 0.4259 | 2.1408 | 4000 | 0.5296 | -5.1372 | -6.2156 | 0.7270 | 1.0783 | -6.2156 | -5.1372 | 0.3103 | 0.2143 | |
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| 0.4141 | 2.3549 | 4400 | 0.5245 | -5.3001 | -6.3996 | 0.7277 | 1.0995 | -6.3996 | -5.3001 | 0.3776 | 0.2775 | |
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| 0.4481 | 2.5690 | 4800 | 0.5253 | -5.2343 | -6.3529 | 0.7307 | 1.1185 | -6.3529 | -5.2343 | 0.4139 | 0.3107 | |
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| 0.3925 | 2.7831 | 5200 | 0.5251 | -5.2099 | -6.3202 | 0.7285 | 1.1103 | -6.3202 | -5.2099 | 0.3386 | 0.2411 | |
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| 0.4044 | 2.9972 | 5600 | 0.5257 | -5.2305 | -6.3460 | 0.7285 | 1.1155 | -6.3460 | -5.2305 | 0.3311 | 0.2347 | |
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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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