| | --- |
| | license: mit |
| | base_model: naver-clova-ix/donut-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - bleu |
| | - wer |
| | model-index: |
| | - name: donut_experiment_bayesian_trial_0 |
| | 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_0 |
| |
|
| | 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: 0.4050 |
| | - Bleu: 0.0639 |
| | - Precisions: [0.79957805907173, 0.7386091127098321, 0.7083333333333334, 0.6765676567656765] |
| | - Brevity Penalty: 0.0876 |
| | - Length Ratio: 0.2912 |
| | - Translation Length: 474 |
| | - Reference Length: 1628 |
| | - Cer: 0.7653 |
| | - Wer: 0.8371 |
| |
|
| | ## 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: 1.2045081648781836e-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: 5 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:| |
| | | 0.9353 | 1.0 | 253 | 0.6228 | 0.0486 | [0.7096774193548387, 0.6053921568627451, 0.5612535612535613, 0.5102040816326531] | 0.0820 | 0.2856 | 465 | 1628 | 0.7751 | 0.8592 | |
| | | 0.462 | 2.0 | 506 | 0.4846 | 0.0568 | [0.7913978494623656, 0.7058823529411765, 0.6609686609686609, 0.6224489795918368] | 0.0820 | 0.2856 | 465 | 1628 | 0.7650 | 0.8423 | |
| | | 0.4071 | 3.0 | 759 | 0.4226 | 0.0626 | [0.7899159663865546, 0.711217183770883, 0.6767955801104972, 0.6459016393442623] | 0.0889 | 0.2924 | 476 | 1628 | 0.7685 | 0.8436 | |
| | | 0.3007 | 4.0 | 1012 | 0.4092 | 0.0638 | [0.7957894736842105, 0.7344497607655502, 0.7008310249307479, 0.6644736842105263] | 0.0883 | 0.2918 | 475 | 1628 | 0.7640 | 0.8397 | |
| | | 0.3114 | 5.0 | 1265 | 0.4050 | 0.0639 | [0.79957805907173, 0.7386091127098321, 0.7083333333333334, 0.6765676567656765] | 0.0876 | 0.2912 | 474 | 1628 | 0.7653 | 0.8371 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.0 |
| | - Pytorch 2.1.0 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.19.1 |
| | |
