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--- |
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library_name: transformers |
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base_model: motheecreator/ViT-GPT2-Image_Captioning_model |
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tags: |
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- generated_from_trainer |
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- image-to-text |
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metrics: |
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- bleu |
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model-index: |
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- name: ViT-GPT2 |
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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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# ViT-GPT2 |
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This model is a fine-tuned version of [motheecreator/ViT-GPT2-Image_Captioning_model](https://huggingface.co./motheecreator/ViT-GPT2-Image_Captioning_model) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.125337 |
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- Rouge2 Precision: None |
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- Rouge2 Recall: None |
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- Rouge2 Fmeasure: 0.155 |
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- Bleu: 9.7054 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 256 |
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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: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Bleu | |
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|:-------------:|:------:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|:------:| |
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| 2.1537 | 0.9993 | 1171 | 2.13666 | None | None | 0.1531 | 9.4673 | |
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| 2.0434 | 1.9985 | 2342 | 2.125337 | None | None | 0.155 | 9.7054 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
