AraBERT_token_classification__AraEval24_merged_rassd_fixed – AI Model by MM2157 | AlphaNeural AI

You can deploy this model and start earning money today!

MM2157/
AraBERT_token_classification__AraEval24_merged_rassd_fixed

like

0

token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

AraBERT_token_classification__AraEval24_merged_rassd_fixed

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

Loss: 0.8835
Precision: 0.0974
Recall: 0.0209
F1: 0.0344
Accuracy: 0.8600

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.6721	1.0	2878	0.7894	0.05	0.0002	0.0005	0.8632
0.6093	2.0	5756	0.7914	0.0841	0.0033	0.0064	0.8636
0.5514	3.0	8634	0.7789	0.1141	0.0042	0.0081	0.8633
0.5117	4.0	11512	0.7879	0.1026	0.0129	0.0229	0.8623
0.4447	5.0	14390	0.8013	0.0881	0.0053	0.0100	0.8628
0.4371	6.0	17268	0.8165	0.1255	0.0151	0.0270	0.8630
0.415	7.0	20146	0.8406	0.0984	0.0116	0.0208	0.8623
0.3919	8.0	23024	0.8537	0.0999	0.0173	0.0295	0.8616
0.3611	9.0	25902	0.8645	0.1039	0.0183	0.0311	0.8614
0.3518	10.0	28780	0.8835	0.0974	0.0209	0.0344	0.8600

Framework versions

Transformers 4.30.2
Pytorch 1.12.1
Datasets 2.13.2
Tokenizers 0.13.3