metadata
library_name: transformers
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
model-index:
- name: donut_checkpoints
results: []
donut_checkpoints
This model is a fine-tuned version of naver-clova-ix/donut-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7296
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.0573 | 1.0 | 250 | 1.4718 |
| 0.6312 | 2.0 | 500 | 0.7169 |
| 0.2924 | 3.0 | 750 | 0.6494 |
| 0.1544 | 4.0 | 1000 | 0.6331 |
| 0.0682 | 5.0 | 1250 | 0.7624 |
| 0.0562 | 6.0 | 1500 | 0.7330 |
| 0.027 | 7.0 | 1750 | 0.7246 |
| 0.0076 | 8.0 | 2000 | 0.6950 |
| 0.0069 | 9.0 | 2250 | 0.7208 |
| 0.008 | 10.0 | 2500 | 0.7296 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1