sinhala-ocr-model-v3
This model is a fine-tuned version of 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
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