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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_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_cocour_new_step10_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_cocour_new_step10_0_90 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4735 |
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- Rewards/chosen: 0.5420 |
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- Rewards/rejected: -2.3019 |
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- Rewards/accuracies: 0.8218 |
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- Rewards/margins: 2.8439 |
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- Logps/rejected: -225.0065 |
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- Logps/chosen: -243.1698 |
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- Logits/rejected: -2.6339 |
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- Logits/chosen: -2.6492 |
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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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| 0.6087 | 0.4158 | 50 | 0.5778 | 0.7419 | -0.5074 | 0.7870 | 1.2493 | -207.0612 | -241.1710 | -2.5285 | -2.5456 | |
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| 0.5039 | 0.8316 | 100 | 0.5226 | 0.2943 | -1.5654 | 0.8056 | 1.8596 | -217.6406 | -245.6472 | -2.5932 | -2.6105 | |
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| 0.2346 | 1.2474 | 150 | 0.4851 | 0.5179 | -1.8870 | 0.8356 | 2.4048 | -220.8566 | -243.4111 | -2.5511 | -2.5729 | |
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| 0.26 | 1.6632 | 200 | 0.4692 | 0.8149 | -1.7120 | 0.8264 | 2.5269 | -219.1066 | -240.4409 | -2.6651 | -2.6766 | |
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| 0.1628 | 2.0790 | 250 | 0.4654 | 0.2522 | -2.4566 | 0.8264 | 2.7088 | -226.5530 | -246.0683 | -2.6802 | -2.6929 | |
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| 0.1808 | 2.4948 | 300 | 0.4721 | 0.8229 | -2.0114 | 0.8241 | 2.8342 | -222.1007 | -240.3612 | -2.6392 | -2.6528 | |
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| 0.1514 | 2.9106 | 350 | 0.4736 | 0.5409 | -2.3033 | 0.8218 | 2.8442 | -225.0204 | -243.1809 | -2.6346 | -2.6500 | |
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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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