---
library_name: transformers
base_model: danush99/Model_TrOCR-Sin-Printed-Text
tags:
- generated_from_trainer
model-index:
- name: checkPoints
  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. -->

# checkPoints

This model is a fine-tuned version of [danush99/Model_TrOCR-Sin-Printed-Text](https://huggingface.co/danush99/Model_TrOCR-Sin-Printed-Text) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2322
- Cer: 0.5629

## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 2.2319        | 1.7544  | 100  | 1.7853          | 0.7027 |
| 0.6266        | 3.5088  | 200  | 1.8948          | 0.7267 |
| 0.2727        | 5.2632  | 300  | 1.9236          | 0.6485 |
| 0.1861        | 7.0175  | 400  | 2.0634          | 0.6453 |
| 0.1811        | 8.7719  | 500  | 2.0956          | 0.6463 |
| 0.1337        | 10.5263 | 600  | 2.2578          | 0.6644 |
| 0.0759        | 12.2807 | 700  | 2.5696          | 0.7128 |
| 0.0797        | 14.0351 | 800  | 2.1449          | 0.6458 |
| 0.0942        | 15.7895 | 900  | 2.1767          | 0.6299 |
| 0.0425        | 17.5439 | 1000 | 2.5660          | 0.6639 |
| 0.0699        | 19.2982 | 1100 | 2.4545          | 0.6781 |
| 0.0707        | 21.0526 | 1200 | 2.7097          | 0.6925 |
| 0.0577        | 22.8070 | 1300 | 2.8215          | 0.7074 |
| 0.0281        | 24.5614 | 1400 | 2.4110          | 0.7004 |
| 0.0336        | 26.3158 | 1500 | 2.3586          | 0.6528 |
| 0.0359        | 28.0702 | 1600 | 2.2111          | 0.6103 |
| 0.0128        | 29.8246 | 1700 | 2.3535          | 0.6307 |
| 0.0560        | 31.5789 | 1800 | 2.3196          | 0.6399 |
| 0.0211        | 33.3333 | 1900 | 2.5897          | 0.6570 |
| 0.0136        | 35.0877 | 2000 | 2.5756          | 0.7019 |
| 0.0039        | 36.8421 | 2100 | 2.9723          | 0.6602 |
| 0.0123        | 38.5965 | 2200 | 2.9204          | 0.6374 |
| 0.0573        | 40.3509 | 2300 | 2.4419          | 0.6508 |
| 0.0178        | 42.1053 | 2400 | 2.3078          | 0.6138 |
| 0.0341        | 43.8596 | 2500 | 2.6973          | 0.6691 |
| 0.0075        | 45.6140 | 2600 | 2.4838          | 0.6530 |
| 0.0176        | 47.3684 | 2700 | 3.2690          | 0.6649 |
| 0.0008        | 49.1228 | 2800 | 3.2363          | 0.6612 |
| 0.0043        | 50.8772 | 2900 | 2.6300          | 0.6441 |
| 0.0031        | 52.6316 | 3000 | 2.7526          | 0.6505 |
| 0.0026        | 54.3860 | 3100 | 2.5666          | 0.6247 |
| 0.0005        | 56.1404 | 3200 | 2.7527          | 0.6369 |
| 0.0009        | 57.8947 | 3300 | 2.6842          | 0.6329 |
| 0.0007        | 59.6491 | 3400 | 2.6928          | 0.6240 |
| 0.0138        | 61.4035 | 3500 | 3.2250          | 0.6513 |
| 0.0009        | 63.1579 | 3600 | 2.4138          | 0.6451 |
| 0.0008        | 64.9123 | 3700 | 2.2832          | 0.6019 |
| 0.0010        | 66.6667 | 3800 | 2.2619          | 0.5974 |
| 0.0003        | 68.4211 | 3900 | 3.0282          | 0.6054 |
| 0.0014        | 70.1754 | 4000 | 2.6130          | 0.6215 |
| 0.0003        | 71.9298 | 4100 | 2.4099          | 0.5805 |
| 0.0004        | 73.6842 | 4200 | 2.5573          | 0.6086 |
| 0.0150        | 75.4386 | 4300 | 2.8885          | 0.6210 |
| 0.0016        | 77.1930 | 4400 | 2.4898          | 0.5994 |
| 0.0002        | 78.9474 | 4500 | 2.7552          | 0.6399 |
| 0.0004        | 80.7018 | 4600 | 2.4722          | 0.5967 |
| 0.0004        | 82.4561 | 4700 | 2.3909          | 0.6006 |
| 0.0003        | 84.2105 | 4800 | 2.5311          | 0.6029 |
| 0.0002        | 85.9649 | 4900 | 2.6945          | 0.5947 |
| 0.0002        | 87.7193 | 5000 | 2.2324          | 0.5644 |
| 0.0002        | 89.4737 | 5100 | 2.2411          | 0.5862 |
| 0.0002        | 91.2281 | 5200 | 2.5429          | 0.6237 |
| 0.0002        | 92.9825 | 5300 | 2.3281          | 0.6059 |
| 0.0001        | 94.7368 | 5400 | 2.3460          | 0.5902 |
| 0.0002        | 96.4912 | 5500 | 2.2796          | 0.5825 |
| 0.0001        | 98.2456 | 5600 | 2.2379          | 0.5830 |
| 0.0011        | 100.0   | 5700 | 2.2377          | 0.5825 |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2