---
base_model: Ransaka/sinhala-ocr-model
tags:
- generated_from_trainer
model-index:
- name: sinhala-ocr-model-v3
  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. -->

# sinhala-ocr-model-v3

This model is a fine-tuned version of [Ransaka/sinhala-ocr-model](https://huggingface.co/Ransaka/sinhala-ocr-model) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7242
- Cer: 0.2764

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.6711        | 6.54  | 500  | 4.9311          | 0.4178 |
| 2.3499        | 13.07 | 1000 | 4.5366          | 0.3482 |
| 1.5601        | 19.61 | 1500 | 4.4634          | 0.3204 |
| 0.987         | 26.14 | 2000 | 4.4804          | 0.3011 |
| 0.6487        | 32.68 | 2500 | 4.6310          | 0.2863 |
| 0.3816        | 39.22 | 3000 | 4.6093          | 0.2788 |
| 0.3494        | 45.75 | 3500 | 4.6291          | 0.2827 |
| 0.2357        | 52.29 | 4000 | 4.6399          | 0.2780 |
| 0.2188        | 58.82 | 4500 | 4.6313          | 0.2798 |
| 0.1413        | 65.36 | 5000 | 4.6828          | 0.2768 |
| 0.0985        | 71.9  | 5500 | 4.7135          | 0.2772 |
| 0.1086        | 78.43 | 6000 | 4.7242          | 0.2764 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.16.0
- Tokenizers 0.15.0