---
library_name: transformers
base_model: microsoft/trocr-small-stage1
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: trocr-finetuned
  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-finetuned

This model is a fine-tuned version of [microsoft/trocr-small-stage1](https://huggingface.co/microsoft/trocr-small-stage1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 9.2627
- Cer: 0.5872
- Wer: 1.0264

## 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: 4e-07
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 13.1378       | 1.0   | 50   | 9.7690          | 0.6655 | 1.2093 |
| 12.3944       | 2.0   | 100  | 9.4940          | 0.6319 | 1.1423 |
| 12.4749       | 3.0   | 150  | 9.3537          | 0.5940 | 1.0691 |
| 10.9977       | 4.0   | 200  | 9.2874          | 0.5884 | 1.0427 |
| 10.8077       | 5.0   | 250  | 9.2627          | 0.5872 | 1.0264 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3