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End of training

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README.md ADDED
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+ ---
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+ base_model: llava-hf/llava-1.5-7b-hf
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+ library_name: peft
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+ license: llama2
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+ metrics:
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+ - bleu
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+ - rouge
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+ tags:
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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ model-index:
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+ - name: llava_test
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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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+ # llava_test
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+
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+ This model is a fine-tuned version of [llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/llava-1.5-7b-hf) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.5219
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+ - Bleu: 0.0477
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+ - Rouge1: 0.2804
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+ - Rouge2: 0.0966
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+ - Rougel: 0.2140
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+ - Bertscore Precision: 0.7005
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+ - Bertscore Recall: 0.7759
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+ - Bertscore F1: 0.7362
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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: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Rougel | Bertscore Precision | Bertscore Recall | Bertscore F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|
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+ | 0.3261 | 10.0 | 10 | 2.5219 | 0.0477 | 0.2804 | 0.0966 | 0.2140 | 0.7005 | 0.7759 | 0.7362 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.0
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+ - Transformers 4.45.2
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.20.1
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