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--- |
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library_name: transformers |
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license: other |
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base_model: llava-hf/llava-v1.6-mistral-7b-hf |
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tags: |
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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: AA_preference_random_0_80 |
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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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# AA_preference_random_0_80 |
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This model is a fine-tuned version of [llava-hf/llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) on the AA_preference_random_0_80 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5567 |
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- Rewards/chosen: -0.0039 |
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- Rewards/rejected: -2.3714 |
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- Rewards/accuracies: 0.8021 |
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- Rewards/margins: 2.3675 |
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- Logps/rejected: -234.5394 |
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- Logps/chosen: -232.6765 |
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- Logits/rejected: -2.2685 |
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- Logits/chosen: -2.3031 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 64 |
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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_steps: 10 |
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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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| 0.576 | 0.4673 | 50 | 0.5725 | 0.8730 | -0.1201 | 0.7318 | 0.9931 | -212.0256 | -223.9073 | -2.4706 | -2.4964 | |
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| 0.508 | 0.9346 | 100 | 0.5507 | -0.2081 | -1.7933 | 0.7865 | 1.5852 | -228.7584 | -234.7186 | -2.4439 | -2.4604 | |
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| 0.2512 | 1.4019 | 150 | 0.5608 | 0.2020 | -1.8022 | 0.7865 | 2.0042 | -228.8469 | -230.6172 | -2.2977 | -2.3324 | |
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| 0.3125 | 1.8692 | 200 | 0.5447 | 0.4722 | -1.5712 | 0.8099 | 2.0434 | -226.5372 | -227.9149 | -2.2994 | -2.3304 | |
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| 0.1519 | 2.3364 | 250 | 0.5571 | 0.1894 | -2.0352 | 0.8047 | 2.2246 | -231.1766 | -230.7427 | -2.3302 | -2.3582 | |
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| 0.1708 | 2.8037 | 300 | 0.5571 | 0.0000 | -2.3612 | 0.8073 | 2.3612 | -234.4372 | -232.6371 | -2.2672 | -2.3019 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.20.3 |
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