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README.md ADDED
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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_0_25
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+ results: []
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+ ---
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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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+
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+ # AA_preference_cocour_0_25
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+
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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_0_25 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5255
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+ - Rewards/chosen: 2.4023
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+ - Rewards/rejected: -0.3121
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+ - Rewards/accuracies: 0.8583
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+ - Rewards/margins: 2.7144
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+ - Logps/rejected: -213.8096
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+ - Logps/chosen: -267.1278
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+ - Logits/rejected: -2.3534
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+ - Logits/chosen: -2.3587
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+ | 0.2339 | 1.4925 | 50 | 0.5196 | 2.3503 | -0.2564 | 0.8500 | 2.6068 | -213.2534 | -267.6478 | -2.2156 | -2.2193 |
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+
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+
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+ ### Framework versions
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+
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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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+ "eval_logps/rejected": -213.8096466064453,
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+ "eval_loss": 0.5255125761032104,
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+ "eval_rewards/accuracies": 0.8583333492279053,
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+ "eval_rewards/chosen": 2.4023120403289795,
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+ "eval_rewards/margins": 2.7143805027008057,
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+ "eval_rewards/rejected": -0.3120681643486023,
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+ "eval_runtime": 61.3371,
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+ "eval_samples_per_second": 15.488,
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+ "eval_steps_per_second": 0.245,
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+ "total_flos": 1167029855846400.0,
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+ "train_loss": 0.3387684075519292,
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+ "train_runtime": 3422.3866,
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+ "train_samples_per_second": 7.492,
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+ "train_steps_per_second": 0.029
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+ }
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