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---
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
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