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--- |
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library_name: transformers |
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license: llama2 |
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base_model: llava-hf/llava-1.5-7b-hf |
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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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metrics: |
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- bleu |
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- rouge |
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model-index: |
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- name: sft-llava-1.5-7b-hf3 |
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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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# sft-llava-1.5-7b-hf3 |
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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: 13.1181 |
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- Bleu: 0.0 |
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- Rouge1: 0.0651 |
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- Rouge2: 0.0043 |
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- Rougel: 0.0508 |
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- Bertscore Precision: 0.6243 |
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- Bertscore Recall: 0.7482 |
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- Bertscore F1: 0.6806 |
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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: 0.0002 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 5.0 |
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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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| 6.903 | 0.3101 | 200 | 22.1793 | 0.0 | 0.0440 | 0.0 | 0.0441 | 0.6243 | 0.7482 | 0.6806 | |
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| 6.585 | 0.6202 | 400 | 27.3559 | 0.0 | 0.0546 | 0.0043 | 0.0425 | 0.6243 | 0.7482 | 0.6806 | |
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| 6.5197 | 0.9302 | 600 | 26.1987 | 0.0 | 0.0546 | 0.0043 | 0.0425 | 0.6243 | 0.7482 | 0.6806 | |
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| 6.2662 | 1.2403 | 800 | 21.1666 | 0.0 | 0.0633 | 0.0043 | 0.0520 | 0.6243 | 0.7482 | 0.6806 | |
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| 6.0303 | 1.5504 | 1000 | 21.0359 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.7602 | 1.8605 | 1200 | 19.0201 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.6359 | 2.1705 | 1400 | 18.6311 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.5176 | 2.4806 | 1600 | 17.9442 | 0.0 | 0.0649 | 0.0043 | 0.0496 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.4608 | 2.7907 | 1800 | 16.6921 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.2881 | 3.1008 | 2000 | 15.3415 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.2429 | 3.4109 | 2200 | 14.8475 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.1929 | 3.7209 | 2400 | 14.2828 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.1259 | 4.0310 | 2600 | 13.8075 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.0379 | 4.3411 | 2800 | 13.4751 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.1071 | 4.6512 | 3000 | 13.2275 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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| 5.1082 | 4.9612 | 3200 | 13.1181 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.2.0a0+81ea7a4 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
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