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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_60 |
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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_60 |
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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_60 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5970 |
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- Rewards/chosen: 1.1265 |
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- Rewards/rejected: -0.9790 |
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- Rewards/accuracies: 0.7882 |
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- Rewards/margins: 2.1055 |
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- Logps/rejected: -220.6737 |
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- Logps/chosen: -235.6061 |
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- Logits/rejected: -2.2225 |
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- Logits/chosen: -2.2440 |
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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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| 0.5547 | 0.6231 | 50 | 0.5781 | 0.9538 | -0.0749 | 0.7222 | 1.0286 | -211.6319 | -237.3329 | -2.4876 | -2.4892 | |
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| 0.2103 | 1.2461 | 100 | 0.6054 | 1.3022 | -0.3360 | 0.7778 | 1.6381 | -214.2431 | -233.8492 | -2.2990 | -2.3139 | |
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| 0.2095 | 1.8692 | 150 | 0.5998 | 1.4071 | -0.5239 | 0.7743 | 1.9310 | -216.1227 | -232.8000 | -2.3737 | -2.3872 | |
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| 0.1498 | 2.4922 | 200 | 0.5972 | 1.0916 | -1.0086 | 0.7847 | 2.1001 | -220.9690 | -235.9549 | -2.2258 | -2.2469 | |
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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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