metadata
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 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