--- license: mit tags: - generated_from_trainer datasets: - textvqa model-index: - name: git-base-textvqa results: [] --- # git-base-textvqa This model is a fine-tuned version of [microsoft/git-base-textvqa](https://huggingface.co/microsoft/git-base-textvqa) on the textvqa dataset. It achieves the following results on the evaluation set: - Loss: 0.0472 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 4 - eval_batch_size: 3 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.9764 | 0.2 | 500 | 0.0499 | | 0.0524 | 0.4 | 1000 | 0.0492 | | 0.0525 | 0.6 | 1500 | 0.0494 | | 0.0531 | 0.8 | 2000 | 0.0480 | | 0.0515 | 1.0 | 2500 | 0.0477 | | 0.0473 | 1.2 | 3000 | 0.0483 | | 0.0479 | 1.4 | 3500 | 0.0477 | | 0.0473 | 1.6 | 4000 | 0.0476 | | 0.0486 | 1.8 | 4500 | 0.0472 | | 0.0471 | 2.0 | 5000 | 0.0473 | | 0.0454 | 2.2 | 5500 | 0.0473 | | 0.0452 | 2.4 | 6000 | 0.0476 | | 0.0438 | 2.6 | 6500 | 0.0475 | | 0.0463 | 2.8 | 7000 | 0.0474 | | 0.0449 | 3.0 | 7500 | 0.0472 | ### Framework versions - Transformers 4.28.0 - Pytorch 2.0.0 - Datasets 2.12.0 - Tokenizers 0.13.3