---
library_name: transformers
base_model: microsoft/trocr-base-str
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: microsoft/trocr-base-str
  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. -->

# microsoft/trocr-base-str

This model is a fine-tuned version of [microsoft/trocr-base-str](https://huggingface.co/microsoft/trocr-base-str) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0856
- Cer: 0.0098
- Wer: 0.0573

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 1.6623        | 1.0   | 217  | 0.4722          | 0.0574 | 0.2340 |
| 0.4122        | 2.0   | 434  | 0.3248          | 0.0378 | 0.1585 |
| 0.1077        | 3.0   | 651  | 0.0898          | 0.0132 | 0.0722 |
| 0.047         | 4.0   | 868  | 0.0848          | 0.0114 | 0.0614 |
| 0.0304        | 5.0   | 1085 | 0.0836          | 0.0122 | 0.0634 |
| 0.0224        | 6.0   | 1302 | 0.0891          | 0.0104 | 0.0566 |
| 0.0154        | 7.0   | 1519 | 0.0873          | 0.0107 | 0.0587 |
| 0.0137        | 8.0   | 1736 | 0.0852          | 0.0102 | 0.0560 |
| 0.0121        | 9.0   | 1953 | 0.0883          | 0.0107 | 0.0634 |
| 0.0095        | 10.0  | 2170 | 0.0829          | 0.0092 | 0.0526 |
| 0.0068        | 11.0  | 2387 | 0.0851          | 0.0091 | 0.0519 |
| 0.0075        | 12.0  | 2604 | 0.0831          | 0.0102 | 0.0600 |
| 0.0055        | 13.0  | 2821 | 0.0824          | 0.0098 | 0.0580 |
| 0.0048        | 14.0  | 3038 | 0.0821          | 0.0099 | 0.0587 |
| 0.0023        | 15.0  | 3255 | 0.0873          | 0.0096 | 0.0553 |
| 0.0018        | 16.0  | 3472 | 0.0835          | 0.0102 | 0.0593 |
| 0.0016        | 17.0  | 3689 | 0.0888          | 0.0100 | 0.0600 |
| 0.0034        | 18.0  | 3906 | 0.0853          | 0.0094 | 0.0553 |
| 0.001         | 19.0  | 4123 | 0.0857          | 0.0096 | 0.0566 |
| 0.0013        | 20.0  | 4340 | 0.0856          | 0.0098 | 0.0573 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.17.0
- Tokenizers 0.19.1