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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_l0_new_step10_0_70 |
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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_l0_new_step10_0_70 |
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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_l0_new_step10_0_70 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5015 |
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- Rewards/chosen: 0.2932 |
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- Rewards/rejected: -2.5932 |
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- Rewards/accuracies: 0.8274 |
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- Rewards/margins: 2.8864 |
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- Logps/rejected: -244.7975 |
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- Logps/chosen: -248.1062 |
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- Logits/rejected: -2.1491 |
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- Logits/chosen: -2.2057 |
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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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| 0.5372 | 0.5348 | 50 | 0.5589 | 0.8885 | -0.7687 | 0.7708 | 1.6573 | -226.5533 | -242.1535 | -2.5558 | -2.5652 | |
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| 0.2535 | 1.0695 | 100 | 0.5072 | 0.6618 | -1.4593 | 0.8155 | 2.1211 | -233.4590 | -244.4205 | -2.3160 | -2.3489 | |
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| 0.2927 | 1.6043 | 150 | 0.5305 | 0.2199 | -2.4527 | 0.8065 | 2.6726 | -243.3929 | -248.8394 | -2.2493 | -2.2896 | |
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| 0.1722 | 2.1390 | 200 | 0.4972 | 0.5435 | -2.1567 | 0.8304 | 2.7003 | -240.4332 | -245.6031 | -2.1267 | -2.1841 | |
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| 0.1412 | 2.6738 | 250 | 0.5014 | 0.2961 | -2.5802 | 0.8214 | 2.8763 | -244.6681 | -248.0778 | -2.1488 | -2.2053 | |
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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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