| | --- |
| | license: mit |
| | base_model: naver-clova-ix/donut-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - bleu |
| | - wer |
| | model-index: |
| | - name: donut_experiment_bayesian_trial_19 |
| | 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. --> |
| |
|
| | # donut_experiment_bayesian_trial_19 |
| |
|
| | This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5754 |
| | - Bleu: 0.0724 |
| | - Precisions: [0.8450413223140496, 0.7892271662763466, 0.7486486486486487, 0.7028753993610224] |
| | - Brevity Penalty: 0.0941 |
| | - Length Ratio: 0.2973 |
| | - Translation Length: 484 |
| | - Reference Length: 1628 |
| | - Cer: 0.7493 |
| | - Wer: 0.8177 |
| |
|
| | ## 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: 1.0668629620167924e-05 |
| | - train_batch_size: 1 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 2 |
| | - 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 | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Cer | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:| |
| | | 0.0069 | 1.0 | 253 | 0.5825 | 0.0710 | [0.8423236514522822, 0.7858823529411765, 0.7418478260869565, 0.6977491961414791] | 0.0928 | 0.2961 | 482 | 1628 | 0.7509 | 0.8197 | |
| | | 0.0113 | 2.0 | 506 | 0.5684 | 0.0703 | [0.841995841995842, 0.785377358490566, 0.7411444141689373, 0.6935483870967742] | 0.0921 | 0.2955 | 481 | 1628 | 0.7505 | 0.8199 | |
| | | 0.0074 | 3.0 | 759 | 0.5754 | 0.0724 | [0.8450413223140496, 0.7892271662763466, 0.7486486486486487, 0.7028753993610224] | 0.0941 | 0.2973 | 484 | 1628 | 0.7493 | 0.8177 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.0 |
| | - Pytorch 2.1.0 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.19.1 |
| | |
