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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_90 |
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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_90 |
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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_90 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5266 |
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- Rewards/chosen: 0.6411 |
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- Rewards/rejected: -1.9030 |
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- Rewards/accuracies: 0.7986 |
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- Rewards/margins: 2.5441 |
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- Logps/rejected: -230.4333 |
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- Logps/chosen: -239.3183 |
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- Logits/rejected: -2.0706 |
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- Logits/chosen: -2.1025 |
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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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| 0.635 | 0.4158 | 50 | 0.5987 | 0.8451 | -0.0388 | 0.7014 | 0.8840 | -211.7915 | -237.2780 | -2.3908 | -2.3899 | |
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| 0.4933 | 0.8316 | 100 | 0.5285 | -0.2263 | -1.8151 | 0.7523 | 1.5888 | -229.5545 | -247.9923 | -1.9128 | -1.9530 | |
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| 0.2495 | 1.2474 | 150 | 0.5427 | 0.5572 | -1.4201 | 0.7593 | 1.9773 | -225.6041 | -240.1570 | -2.0983 | -2.1232 | |
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| 0.2753 | 1.6632 | 200 | 0.5260 | 0.5776 | -1.6735 | 0.7870 | 2.2511 | -228.1382 | -239.9529 | -1.9752 | -2.0068 | |
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| 0.1584 | 2.0790 | 250 | 0.5118 | 0.5255 | -1.9057 | 0.7940 | 2.4312 | -230.4605 | -240.4746 | -2.0354 | -2.0689 | |
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| 0.1572 | 2.4948 | 300 | 0.5261 | 0.7582 | -1.7260 | 0.7986 | 2.4842 | -228.6629 | -238.1469 | -2.0616 | -2.0941 | |
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| 0.1557 | 2.9106 | 350 | 0.5265 | 0.6414 | -1.9061 | 0.7986 | 2.5475 | -230.4645 | -239.3154 | -2.0706 | -2.1026 | |
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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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