---
base_model: microsoft/trocr-base-stage1
tags:
- generated_from_trainer
model-index:
- name: IS557_TrOCR_AllData
  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. -->

# IS557_TrOCR_AllData

This model is a fine-tuned version of [microsoft/trocr-base-stage1](https://huggingface.co/microsoft/trocr-base-stage1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0124
- Cer: 0.1764

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.4421        | 0.0708 | 200  | 4.1713          | 0.6172 |
| 3.2966        | 0.1415 | 400  | 3.1228          | 0.5064 |
| 2.5955        | 0.2123 | 600  | 2.7626          | 0.3949 |
| 2.201         | 0.2831 | 800  | 2.4729          | 0.4258 |
| 1.5876        | 0.3539 | 1000 | 2.2295          | 0.3097 |
| 2.7774        | 0.4246 | 1200 | 2.1112          | 0.3092 |
| 2.7995        | 0.4954 | 1400 | 2.1286          | 0.3070 |
| 1.5241        | 0.5662 | 1600 | 1.8915          | 0.2534 |
| 0.9877        | 0.6369 | 1800 | 1.8091          | 0.2624 |
| 1.21          | 0.7077 | 2000 | 1.7322          | 0.2552 |
| 1.5582        | 0.7785 | 2200 | 1.6645          | 0.2445 |
| 1.1392        | 0.8493 | 2400 | 1.6458          | 0.2294 |
| 1.8181        | 0.9200 | 2600 | 1.5874          | 0.2313 |
| 1.2517        | 0.9908 | 2800 | 1.5736          | 0.2361 |
| 1.2004        | 1.0616 | 3000 | 1.5693          | 0.2344 |
| 1.4357        | 1.1323 | 3200 | 1.5447          | 0.2190 |
| 1.1354        | 1.2031 | 3400 | 1.4577          | 0.3232 |
| 0.853         | 1.2739 | 3600 | 1.4034          | 0.2166 |
| 1.4631        | 1.3447 | 3800 | 1.4105          | 0.2093 |
| 2.3234        | 1.4154 | 4000 | 1.3813          | 0.2044 |
| 0.6976        | 1.4862 | 4200 | 1.3505          | 0.2088 |
| 1.4337        | 1.5570 | 4400 | 1.3338          | 0.2079 |
| 1.0502        | 1.6277 | 4600 | 1.3044          | 0.1900 |
| 1.2216        | 1.6985 | 4800 | 1.2883          | 0.2176 |
| 1.0111        | 1.7693 | 5000 | 1.2530          | 0.1977 |
| 0.9992        | 1.8401 | 5200 | 1.2245          | 0.2064 |
| 0.9941        | 1.9108 | 5400 | 1.2187          | 0.1933 |
| 1.4861        | 1.9816 | 5600 | 1.1961          | 0.1827 |
| 1.1703        | 2.0524 | 5800 | 1.1776          | 0.1927 |
| 0.8935        | 2.1231 | 6000 | 1.1617          | 0.1891 |
| 2.5386        | 2.1939 | 6200 | 1.1686          | 0.1823 |
| 0.4705        | 2.2647 | 6400 | 1.1259          | 0.1843 |
| 1.2777        | 2.3355 | 6600 | 1.1228          | 0.1882 |
| 0.6823        | 2.4062 | 6800 | 1.1035          | 0.1787 |
| 1.2498        | 2.4770 | 7000 | 1.0976          | 0.1814 |
| 0.4579        | 2.5478 | 7200 | 1.0839          | 0.1721 |
| 0.9005        | 2.6185 | 7400 | 1.0695          | 0.1817 |
| 0.8045        | 2.6893 | 7600 | 1.0513          | 0.1745 |
| 1.3044        | 2.7601 | 7800 | 1.0336          | 0.1814 |
| 1.0797        | 2.8309 | 8000 | 1.0275          | 0.1846 |
| 0.3826        | 2.9016 | 8200 | 1.0178          | 0.1817 |
| 0.6175        | 2.9724 | 8400 | 1.0124          | 0.1764 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1