| --- |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: TrOCRTraining2 |
| 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. --> |
|
|
| # TrOCRTraining2 |
|
|
| This model is a fine-tuned version of [microsoft/trocr-base-stage1](https://huggingface.co/microsoft/trocr-base-stage1) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4589 |
| - Cer: 0.0115 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Cer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 0.7331 | 1.06 | 50 | 0.8204 | 0.1775 | |
| | 0.4908 | 2.13 | 100 | 0.5457 | 0.0229 | |
| | 0.4912 | 3.19 | 150 | 0.5845 | 0.0229 | |
| | 0.4713 | 4.26 | 200 | 0.5433 | 0.0137 | |
| | 0.4435 | 5.32 | 250 | 0.4988 | 0.0126 | |
| | 0.4152 | 6.38 | 300 | 0.5058 | 0.0137 | |
| | 0.3026 | 7.45 | 350 | 0.4947 | 0.0126 | |
| | 0.4133 | 8.51 | 400 | 0.4988 | 0.0115 | |
| | 0.4029 | 9.57 | 450 | 0.4906 | 0.0160 | |
| | 0.3439 | 10.64 | 500 | 0.4790 | 0.0160 | |
| | 0.3386 | 11.7 | 550 | 0.4661 | 0.0103 | |
| | 0.3511 | 12.77 | 600 | 0.4617 | 0.0115 | |
| | 0.374 | 13.83 | 650 | 0.4629 | 0.0149 | |
| | 0.3357 | 14.89 | 700 | 0.4589 | 0.0115 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.28.1 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.12.0 |
| - Tokenizers 0.13.3 |
|
|
