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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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<!-- 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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# llava_test |
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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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## 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: 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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### Training results |
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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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### Framework versions |
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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 |
