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# legal_text_classifier_50_classA

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4503
- F1: 0.6348

## 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: 2e-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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.7149        | 1.0   | 1582  | 0.9541          | 0.6683 |
| 0.5199        | 2.0   | 3164  | 1.1329          | 0.6635 |
| 0.4678        | 3.0   | 4746  | 1.1535          | 0.6516 |
| 0.4338        | 4.0   | 6328  | 1.1667          | 0.6516 |
| 0.4052        | 5.0   | 7910  | 1.2930          | 0.6492 |
| 0.3817        | 6.0   | 9492  | 1.3078          | 0.6372 |
| 0.3798        | 7.0   | 11074 | 1.3624          | 0.6325 |
| 0.3738        | 8.0   | 12656 | 1.3872          | 0.6325 |
| 0.3612        | 9.0   | 14238 | 1.4459          | 0.6348 |
| 0.3501        | 10.0  | 15820 | 1.4503          | 0.6348 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "legal_text_classifier_50_classA", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

legal\_text\_classifier\_50\_classA
===================================


This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.4503
* F1: 0.6348


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: 2e-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: 10


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 10 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 10 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 10### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1