| | --- |
| | license: mit |
| | base_model: naver-clova-ix/donut-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - bleu |
| | - wer |
| | model-index: |
| | - name: donut_experiment_bayesian_trial_12 |
| | 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_12 |
| |
|
| | 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: 0.5083 |
| | - Bleu: 0.0675 |
| | - Precisions: [0.8421052631578947, 0.7822966507177034, 0.7423822714681441, 0.7006578947368421] |
| | - Brevity Penalty: 0.0883 |
| | - Length Ratio: 0.2918 |
| | - Translation Length: 475 |
| | - Reference Length: 1628 |
| | - Cer: 0.7537 |
| | - Wer: 0.8211 |
| |
|
| | ## 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: 1.2643161326759464e-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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:| |
| | | 0.0251 | 1.0 | 253 | 0.4936 | 0.0660 | [0.8375527426160337, 0.7673860911270983, 0.7277777777777777, 0.6897689768976898] | 0.0876 | 0.2912 | 474 | 1628 | 0.7600 | 0.8274 | |
| | | 0.0144 | 2.0 | 506 | 0.4987 | 0.0683 | [0.8445378151260504, 0.7852028639618138, 0.7458563535911602, 0.7049180327868853] | 0.0889 | 0.2924 | 476 | 1628 | 0.7515 | 0.8189 | |
| | | 0.0089 | 3.0 | 759 | 0.5083 | 0.0675 | [0.8421052631578947, 0.7822966507177034, 0.7423822714681441, 0.7006578947368421] | 0.0883 | 0.2918 | 475 | 1628 | 0.7537 | 0.8211 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.0 |
| | - Pytorch 2.1.0 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.19.1 |
| | |
