metadata
library_name: transformers
license: mit
base_model: hf-tuner/donut-efficient-test2
tags:
- generated_from_trainer
model-index:
- name: donut-classification-turbo
results: []
datasets:
- hf-tuner/rvl-cdip-document-classification
language:
- en
- ko
- ja
- zh
metrics:
- exact_match
- accuracy
- confusion_matrix
pipeline_tag: image-text-to-text
donut-classification-turbo
This model is a fine-tuned version of donut-base-finetuned-rvl-cdip on rvl-cdip-document-classification dataset. It achieves the following results on the evaluation set:
- Loss: 0.0499
- Accuracy: 93.34%
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1319 | 0.5 | 2000 | 0.1200 |
| 0.1365 | 1.0 | 4000 | 0.0845 |
| 0.1203 | 1.5 | 6000 | 0.0751 |
| 0.1128 | 2.0 | 8000 | 0.0677 |
| 0.0734 | 2.5 | 10000 | 0.0541 |
| 0.0707 | 3.0 | 12000 | 0.0499 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1