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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_cosi_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_cosi_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_cosi_new_step10_0_80 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5448 |
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- Rewards/chosen: 0.4294 |
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- Rewards/rejected: -2.4664 |
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- Rewards/accuracies: 0.7969 |
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- Rewards/margins: 2.8958 |
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- Logps/rejected: -238.7556 |
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- Logps/chosen: -244.1195 |
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- Logits/rejected: -2.2467 |
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- Logits/chosen: -2.2820 |
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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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| 0.5529 | 0.4673 | 50 | 0.5947 | 0.8739 | -0.2594 | 0.7318 | 1.1333 | -216.6857 | -239.6745 | -2.0297 | -2.0593 | |
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| 0.5159 | 0.9346 | 100 | 0.5286 | -0.2159 | -2.0191 | 0.7812 | 1.8031 | -234.2824 | -250.5727 | -1.9168 | -1.9646 | |
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| 0.2666 | 1.4019 | 150 | 0.5667 | 0.7904 | -1.6811 | 0.7891 | 2.4715 | -230.9029 | -240.5096 | -2.2443 | -2.2847 | |
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| 0.3127 | 1.8692 | 200 | 0.5356 | 0.6480 | -1.8158 | 0.8047 | 2.4639 | -232.2502 | -241.9330 | -2.3879 | -2.4148 | |
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| 0.152 | 2.3364 | 250 | 0.5442 | 0.6088 | -2.0845 | 0.7891 | 2.6933 | -234.9365 | -242.3255 | -2.2443 | -2.2814 | |
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| 0.1431 | 2.8037 | 300 | 0.5450 | 0.4225 | -2.4743 | 0.7943 | 2.8968 | -238.8347 | -244.1887 | -2.2467 | -2.2822 | |
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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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