---
base_model: kavg/TrOCR-SIN-DeiT
tags:
- generated_from_trainer
model-index:
- name: TrOCR-SIN-DeiT-Handwritten-Beam10
  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-SIN-DeiT-Handwritten-Beam10

This model is a fine-tuned version of [kavg/TrOCR-SIN-DeiT](https://huggingface.co/kavg/TrOCR-SIN-DeiT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2754
- Cer: 0.5246

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Cer    | Validation Loss |
|:-------------:|:-----:|:----:|:------:|:---------------:|
| 0.9957        | 1.75  | 100  | 0.6176 | 1.6796          |
| 0.0678        | 3.51  | 200  | 0.5996 | 1.7777          |
| 0.1315        | 5.26  | 300  | 0.6794 | 2.1444          |
| 0.0668        | 7.02  | 400  | 0.6363 | 2.0162          |
| 0.0656        | 8.77  | 500  | 0.6046 | 1.9573          |
| 0.0612        | 10.53 | 600  | 0.6330 | 1.9388          |
| 0.0454        | 12.28 | 700  | 0.6679 | 3.0649          |
| 0.004         | 14.04 | 800  | 0.5814 | 2.0252          |
| 0.0034        | 15.79 | 900  | 0.5492 | 2.0399          |
| 0.0336        | 17.54 | 1000 | 0.6041 | 2.9769          |
| 0.0135        | 19.3  | 1100 | 0.5742 | 1.9405          |
| 0.0012        | 21.05 | 1200 | 0.5959 | 2.5722          |
| 0.0143        | 22.81 | 1300 | 0.5527 | 2.0862          |
| 0.0018        | 24.56 | 1400 | 0.5764 | 2.4146          |
| 0.0064        | 26.32 | 1500 | 0.5647 | 2.0710          |
| 0.0006        | 28.07 | 1600 | 0.5472 | 2.1849          |
| 0.0004        | 29.82 | 1700 | 0.5547 | 2.4497          |
| 0.0001        | 31.58 | 1800 | 0.5430 | 2.0830          |
| 0.0215        | 33.33 | 1900 | 0.5560 | 2.5979          |
| 0.0           | 35.09 | 2000 | 0.5525 | 2.4792          |
| 0.0           | 36.84 | 2100 | 0.5428 | 2.4779          |
| 0.0           | 38.6  | 2200 | 0.5438 | 2.7873          |
| 0.0           | 40.35 | 2300 | 0.5552 | 2.9236          |
| 0.0           | 42.11 | 2400 | 0.5246 | 2.2754          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1