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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- textvqa
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model-index:
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- name: git-base-textvqa
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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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# git-base-textvqa
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This model is a fine-tuned version of [microsoft/git-base-textvqa](https://huggingface.co/microsoft/git-base-textvqa) on the textvqa dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0472
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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: 4
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- eval_batch_size: 3
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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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- num_epochs: 3
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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 |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.9764 | 0.2 | 500 | 0.0499 |
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| 0.0524 | 0.4 | 1000 | 0.0492 |
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| 0.0525 | 0.6 | 1500 | 0.0494 |
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| 0.0531 | 0.8 | 2000 | 0.0480 |
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| 0.0515 | 1.0 | 2500 | 0.0477 |
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| 0.0473 | 1.2 | 3000 | 0.0483 |
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| 0.0479 | 1.4 | 3500 | 0.0477 |
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| 0.0473 | 1.6 | 4000 | 0.0476 |
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| 0.0486 | 1.8 | 4500 | 0.0472 |
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| 0.0471 | 2.0 | 5000 | 0.0473 |
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| 0.0454 | 2.2 | 5500 | 0.0473 |
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| 0.0452 | 2.4 | 6000 | 0.0476 |
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| 0.0438 | 2.6 | 6500 | 0.0475 |
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| 0.0463 | 2.8 | 7000 | 0.0474 |
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| 0.0449 | 3.0 | 7500 | 0.0472 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.0
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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