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# ArOCRv4

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5811
- Cer: 0.1249

## 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
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 3.103         | 1.18  | 1000 | 8.0852          | 11.5974 |
| 1.2535        | 2.36  | 2000 | 2.0400          | 0.4904  |
| 0.5682        | 3.55  | 3000 | 1.9336          | 0.2145  |
| 0.3038        | 4.73  | 4000 | 1.5811          | 0.1249  |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.9.1
- Datasets 2.1.0
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "model-index": [{"name": "ArOCRv4", "results": []}]}
transformers pytorch tensorboard vision-encoder-decoder generated_from_trainer doi:10.57967/hf/0018 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #vision-encoder-decoder #generated_from_trainer #doi-10.57967/hf/0018 #endpoints_compatible #region-us 

ArOCRv4
=======


This model is a fine-tuned version of [](URL on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 1.5811
* Cer: 0.1249


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
* num\_epochs: 5
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.9.1
* Datasets 2.1.0
* Tokenizers 0.11.6



### 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
* num\_epochs: 5
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.9.1
* Datasets 2.1.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #vision-encoder-decoder #generated_from_trainer #doi-10.57967/hf/0018 #endpoints_compatible #region-us 
 ### 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
* num\_epochs: 5
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.9.1
* Datasets 2.1.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #vision-encoder-decoder #generated_from_trainer #doi-10.57967/hf/0018 #endpoints_compatible #region-us 
### 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
* num\_epochs: 5
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.9.1
* Datasets 2.1.0
* Tokenizers 0.11.6