donut_finetuned_chart
This model is a fine-tuned version of naver-clova-ix/donut-base on an chart images dataset. It achieves the following results on the evaluation set:
- Loss: 0.4957
- Cer: 0.2318
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: 2.3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 3.4943 | 1.0 | 166 | 0.6634 | 0.2341 |
| 0.475 | 2.0 | 333 | 0.5370 | 0.2320 |
| 0.3009 | 3.0 | 500 | 0.5051 | 0.2318 |
| 0.2611 | 3.98 | 664 | 0.4957 | 0.2318 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3