| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - textvqa |
| | model-index: |
| | - name: git-base-textvqa |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # 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 |
| |
|
