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

This model is a fine-tuned version of [kavg/TrOCR-SIN](https://huggingface.co/kavg/TrOCR-SIN) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4199
- Cer: 0.5981

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Cer    | Validation Loss |
|:-------------:|:-----:|:----:|:------:|:---------------:|
| 1.1305        | 1.72  | 50   | 0.7056 | 2.0648          |
| 0.5468        | 3.45  | 100  | 0.7023 | 1.9332          |
| 0.0732        | 5.17  | 150  | 0.6624 | 2.2013          |
| 0.0995        | 6.9   | 200  | 0.6756 | 2.2015          |
| 0.1715        | 8.62  | 250  | 0.6602 | 2.0091          |
| 0.1086        | 10.34 | 300  | 0.6672 | 2.2239          |
| 0.0798        | 12.07 | 350  | 0.6839 | 2.0926          |
| 0.0194        | 13.79 | 400  | 0.6926 | 2.2650          |
| 0.0453        | 15.52 | 450  | 0.7223 | 2.4613          |
| 0.0579        | 17.24 | 500  | 0.6931 | 2.3523          |
| 0.0301        | 18.97 | 550  | 0.6215 | 2.1677          |
| 0.0215        | 20.69 | 600  | 0.6602 | 2.2610          |
| 0.0112        | 22.41 | 650  | 0.6415 | 2.2070          |
| 0.0048        | 24.14 | 700  | 0.6363 | 2.2219          |
| 0.0117        | 25.86 | 750  | 0.6609 | 2.2341          |
| 0.0034        | 27.59 | 800  | 0.6829 | 2.4177          |
| 0.0184        | 29.31 | 850  | 0.6826 | 2.3418          |
| 0.0108        | 31.03 | 900  | 0.6682 | 2.3715          |
| 0.0152        | 32.76 | 950  | 0.6542 | 2.2079          |
| 0.0019        | 34.48 | 1000 | 0.6365 | 2.2173          |
| 0.0009        | 36.21 | 1050 | 0.6574 | 2.4185          |
| 0.0013        | 37.93 | 1100 | 0.6520 | 2.3515          |
| 0.0005        | 39.66 | 1150 | 0.6081 | 2.2393          |
| 0.0003        | 41.38 | 1200 | 0.6632 | 2.7642          |
| 0.0003        | 43.1  | 1250 | 0.6313 | 2.2789          |
| 0.0002        | 44.83 | 1300 | 0.6360 | 2.3862          |
| 0.0004        | 46.55 | 1350 | 0.6228 | 2.3372          |
| 0.0001        | 48.28 | 1400 | 0.6542 | 2.3822          |
| 0.0003        | 50.0  | 1450 | 2.3609 | 0.6480          |
| 0.0015        | 51.72 | 1500 | 2.6877 | 0.6520          |
| 0.0352        | 53.45 | 1550 | 3.3146 | 0.6826          |
| 0.0085        | 55.17 | 1600 | 2.8430 | 0.6901          |
| 0.0004        | 56.9  | 1650 | 3.0267 | 0.6654          |
| 0.0006        | 58.62 | 1700 | 2.3768 | 0.6589          |
| 0.0013        | 60.34 | 1750 | 2.4242 | 0.6717          |
| 0.0033        | 62.07 | 1800 | 2.5133 | 0.6512          |
| 0.0002        | 63.79 | 1850 | 2.4018 | 0.6604          |
| 0.0006        | 65.52 | 1900 | 2.8438 | 0.6679          |
| 0.0006        | 67.24 | 1950 | 2.4073 | 0.6482          |
| 0.0001        | 68.97 | 2000 | 2.7375 | 0.6510          |
| 0.0002        | 70.69 | 2050 | 2.4250 | 0.6146          |
| 0.0001        | 72.41 | 2100 | 2.7045 | 0.6604          |
| 0.0001        | 74.14 | 2150 | 3.3714 | 0.6597          |
| 0.0001        | 75.86 | 2200 | 2.9585 | 0.6936          |
| 0.0           | 77.59 | 2250 | 2.5378 | 0.6131          |
| 0.0136        | 79.31 | 2300 | 2.6351 | 0.6146          |
| 0.0           | 81.03 | 2350 | 2.5288 | 0.6116          |
| 0.0001        | 82.76 | 2400 | 2.4601 | 0.6338          |
| 0.0002        | 84.48 | 2450 | 2.4646 | 0.6248          |
| 0.0           | 86.21 | 2500 | 2.8099 | 0.6542          |
| 0.0           | 87.93 | 2550 | 2.7981 | 0.6781          |
| 0.0           | 89.66 | 2600 | 2.4607 | 0.6200          |
| 0.0           | 91.38 | 2650 | 2.5363 | 0.6612          |
| 0.0096        | 93.1  | 2700 | 2.4875 | 0.6113          |
| 0.0           | 94.83 | 2750 | 2.4574 | 0.6268          |
| 0.0           | 96.55 | 2800 | 2.4199 | 0.5981          |
| 0.0           | 98.28 | 2850 | 2.4452 | 0.6181          |
| 0.0           | 100.0 | 2900 | 2.4369 | 0.6036          |


### Framework versions

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