---
base_model: kavg/TrOCR-SIN-DeiT
tags:
- generated_from_trainer
model-index:
- name: TrOCR-SIN-DeiT-Handwritten-Beam10-maxseq128
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# TrOCR-SIN-DeiT-Handwritten-Beam10-maxseq128

This model is a fine-tuned version of [kavg/TrOCR-SIN-DeiT](https://huggingface.co./kavg/TrOCR-SIN-DeiT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7352
- Cer: 0.5340

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Cer    | Validation Loss |
|:-------------:|:-----:|:----:|:------:|:---------------:|
| 0.9936        | 1.75  | 100  | 0.6193 | 1.6907          |
| 0.0819        | 3.51  | 200  | 0.6011 | 1.8343          |
| 0.1437        | 5.26  | 300  | 0.6579 | 2.1956          |
| 0.0857        | 7.02  | 400  | 0.6435 | 2.6580          |
| 0.0531        | 8.77  | 500  | 0.5595 | 1.9046          |
| 0.1282        | 10.53 | 600  | 0.6121 | 2.1264          |
| 0.0247        | 12.28 | 700  | 0.6218 | 2.5938          |
| 0.0071        | 14.04 | 800  | 0.6402 | 2.2984          |
| 0.0235        | 15.79 | 900  | 0.5961 | 2.3736          |
| 0.152         | 17.54 | 1000 | 0.5674 | 2.0205          |
| 0.0521        | 19.3  | 1100 | 0.5802 | 2.5917          |
| 0.0047        | 21.05 | 1200 | 0.6116 | 2.6910          |
| 0.065         | 22.81 | 1300 | 0.5757 | 2.2894          |
| 0.0313        | 24.56 | 1400 | 0.5647 | 2.6897          |
| 0.0586        | 26.32 | 1500 | 0.5398 | 2.0499          |
| 0.0015        | 28.07 | 1600 | 0.5505 | 2.3662          |
| 0.0125        | 29.82 | 1700 | 0.6250 | 2.1673          |
| 0.0207        | 31.58 | 1800 | 0.5674 | 2.0626          |
| 0.0015        | 33.33 | 1900 | 0.6260 | 2.9868          |
| 0.0004        | 35.09 | 2000 | 0.5792 | 2.5184          |
| 0.001         | 36.84 | 2100 | 0.5557 | 2.8804          |
| 0.0134        | 38.6  | 2200 | 0.6166 | 2.7627          |
| 0.0017        | 40.35 | 2300 | 0.5477 | 2.2333          |
| 0.0046        | 42.11 | 2400 | 0.5871 | 3.2010          |
| 0.0003        | 43.86 | 2500 | 0.5485 | 2.7037          |
| 0.0007        | 45.61 | 2600 | 0.5340 | 2.7352          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1