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---
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
|