| | --- |
| | base_model: microsoft/trocr-base-stage1 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: TrOCR_0216 |
| | 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. --> |
| |
|
| | # TrOCR_0216 |
| | |
| | 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: 1.8095 |
| | - Cer: 0.0608 |
| | |
| | ## 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: 10 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Cer | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 0.626 | 0.5 | 500 | 0.9106 | 0.1848 | |
| | | 0.5456 | 1.0 | 1000 | 0.7220 | 0.1927 | |
| | | 0.4588 | 1.5 | 1500 | 0.7064 | 0.1240 | |
| | | 0.6771 | 2.0 | 2000 | 0.7207 | 0.2169 | |
| | | 0.3778 | 2.5 | 2500 | 0.6689 | 0.1283 | |
| | | 0.4543 | 3.0 | 3000 | 0.6833 | 0.3052 | |
| | | 0.4428 | 3.5 | 3500 | 0.6604 | 0.0893 | |
| | | 0.4899 | 4.0 | 4000 | 0.7024 | 0.0692 | |
| | | 0.2548 | 4.5 | 4500 | 1.0137 | 0.1599 | |
| | | 0.0851 | 5.0 | 5000 | 1.8095 | 0.0608 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.1+cu121 |
| | - Datasets 2.13.0 |
| | - Tokenizers 0.15.0 |
| | |
