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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_cocour_new_step10_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_cocour_new_step10_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_cocour_new_step10_0_80 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5250 |
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- Rewards/chosen: 0.5658 |
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- Rewards/rejected: -2.2697 |
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- Rewards/accuracies: 0.8307 |
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- Rewards/margins: 2.8355 |
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- Logps/rejected: -237.9764 |
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- Logps/chosen: -250.5795 |
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- Logits/rejected: -2.1447 |
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- Logits/chosen: -2.1680 |
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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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| 0.572 | 0.4673 | 50 | 0.5720 | 1.0708 | -0.2185 | 0.7578 | 1.2893 | -217.4643 | -245.5292 | -2.5291 | -2.5309 | |
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| 0.4997 | 0.9346 | 100 | 0.5102 | 0.8653 | -0.9135 | 0.7865 | 1.7788 | -224.4143 | -247.5850 | -2.1776 | -2.2008 | |
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| 0.2873 | 1.4019 | 150 | 0.5675 | 1.0559 | -1.2279 | 0.7891 | 2.2838 | -227.5579 | -245.6786 | -2.2632 | -2.2750 | |
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| 0.2853 | 1.8692 | 200 | 0.5163 | 0.7188 | -1.7114 | 0.8203 | 2.4302 | -232.3931 | -249.0491 | -2.1251 | -2.1478 | |
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| 0.1541 | 2.3364 | 250 | 0.5271 | 0.5977 | -2.1434 | 0.8177 | 2.7411 | -236.7135 | -250.2604 | -2.2153 | -2.2352 | |
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| 0.1566 | 2.8037 | 300 | 0.5242 | 0.5568 | -2.2821 | 0.8307 | 2.8389 | -238.1007 | -250.6694 | -2.1442 | -2.1674 | |
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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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