---
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: 0.1131
- Cer: 0.0102
- Wer: 0.0601

## 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: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 1.8737        | 1.0   | 173  | 0.5194          | 0.0668 | 0.2809 |
| 0.3674        | 2.0   | 346  | 0.1408          | 0.0183 | 0.1015 |
| 0.0907        | 3.0   | 519  | 0.1151          | 0.0150 | 0.0821 |
| 0.0584        | 4.0   | 692  | 0.0987          | 0.0140 | 0.0778 |
| 0.0374        | 5.0   | 865  | 0.1041          | 0.0113 | 0.0711 |
| 0.0237        | 6.0   | 1038 | 0.0988          | 0.0102 | 0.0626 |
| 0.0172        | 7.0   | 1211 | 0.0981          | 0.0109 | 0.0643 |
| 0.0177        | 8.0   | 1384 | 0.1019          | 0.0109 | 0.0643 |
| 0.0134        | 9.0   | 1557 | 0.1080          | 0.0106 | 0.0643 |
| 0.009         | 10.0  | 1730 | 0.1023          | 0.0094 | 0.0567 |
| 0.0092        | 11.0  | 1903 | 0.1021          | 0.0090 | 0.0558 |
| 0.0085        | 12.0  | 2076 | 0.1057          | 0.0105 | 0.0635 |
| 0.006         | 13.0  | 2249 | 0.1055          | 0.0107 | 0.0618 |
| 0.006         | 14.0  | 2422 | 0.1066          | 0.0105 | 0.0618 |
| 0.0046        | 15.0  | 2595 | 0.1110          | 0.0103 | 0.0618 |
| 0.0038        | 16.0  | 2768 | 0.1093          | 0.0101 | 0.0601 |
| 0.0028        | 17.0  | 2941 | 0.1095          | 0.0099 | 0.0575 |
| 0.0026        | 18.0  | 3114 | 0.1095          | 0.0099 | 0.0575 |
| 0.0021        | 19.0  | 3287 | 0.1088          | 0.0097 | 0.0584 |
| 0.0017        | 20.0  | 3460 | 0.1127          | 0.0105 | 0.0601 |
| 0.0014        | 21.0  | 3633 | 0.1127          | 0.0099 | 0.0575 |
| 0.0015        | 22.0  | 3806 | 0.1129          | 0.0101 | 0.0592 |
| 0.0008        | 23.0  | 3979 | 0.1132          | 0.0101 | 0.0592 |
| 0.0008        | 24.0  | 4152 | 0.1132          | 0.0102 | 0.0601 |
| 0.0006        | 25.0  | 4325 | 0.1131          | 0.0102 | 0.0601 |


### Framework versions

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