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# AraGPT2-finetuned-crossVal-fnd

This model is a fine-tuned version of [aubmindlab/aragpt2-mega-detector-long](https://huggingface.co/aubmindlab/aragpt2-mega-detector-long) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2251
- Macro F1: 0.9002
- Accuracy: 0.9041
- Precision: 0.9040
- Recall: 0.8972

## 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: 32
- eval_batch_size: 64
- seed: 123
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
| No log        | 1.0   | 399  | 0.2251          | 0.9002   | 0.9041   | 0.9040    | 0.8972 |
| 0.3416        | 2.0   | 798  | 0.2335          | 0.8962   | 0.9008   | 0.9030    | 0.8916 |


### Framework versions

- Transformers 4.12.2
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall"], "model-index": [{"name": "AraGPT2-finetuned-crossVal-fnd", "results": []}]}
transformers pytorch tensorboard electra text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #electra #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

AraGPT2-finetuned-crossVal-fnd
==============================


This model is a fine-tuned version of aubmindlab/aragpt2-mega-detector-long on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2251
* Macro F1: 0.9002
* Accuracy: 0.9041
* Precision: 0.9040
* Recall: 0.8972


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: 32
* eval\_batch\_size: 64
* seed: 123
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.12.2
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 64
* seed: 123
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.12.2
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #electra #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: 32
* eval\_batch\_size: 64
* seed: 123
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.12.2
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #electra #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: 32
* eval\_batch\_size: 64
* seed: 123
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.12.2
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.10.3