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Model_TrOCR-Sin-Printed-Text
danush99/Model_TrOCR-Sin-Printed-Text
Model_TrOCR-Sin-Printed-Text is a machine learning model from danush99. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- vision-encoder-decoder
- Access
- Public
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026
- SHA
- 14836a6e
Model card
From the Hugging Face model README
<!-- 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)
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4335
- Cer: 0.1445
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
- training_steps: 75000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss |
|---|---|---|---|---|
| 1.3019 | 1.78 | 5000 | 0.6416 | 1.7769 |
| 0.6387 | 3.55 | 10000 | 0.4048 | 0.8457 |
| 0.3402 | 5.33 | 15000 | 0.2808 | 0.6898 |
| 0.1332 | 7.11 | 20000 | 0.2377 | 0.5765 |
| 0.1141 | 8.89 | 25000 | 0.2223 | 0.4460 |
| 0.0481 | 10.66 | 30000 | 0.1868 | 0.4128 |
| 0.0391 | 12.44 | 35000 | 0.1563 | 0.4172 |
| 0.0357 | 14.22 | 40000 | 0.1981 | 0.4756 |
| 0.0215 | 16.0 | 45000 | 0.1983 | 0.5838 |
| 0.0129 | 17.77 | 50000 | 0.1757 | 0.5511 |
| 0.0087 | 19.55 | 55000 | 0.1699 | 0.5568 |
| 0.003 | 21.33 | 60000 | 0.1648 | 0.4532 |
| 0.0042 | 23.11 | 65000 | 0.1582 | 0.4650 |
| 0.0066 | 24.88 | 70000 | 0.1654 | 0.4740 |
| 0.0014 | 26.66 | 75000 | 0.1448 | 0.4337 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1
- Type
- vision-encoder-decoder
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026