This model is a fine-tuned version of distilbert/distilbert-base-uncased on the hate_speech18 dataset. It achieves the following results on the evaluation set:

Loss: 1.0451
Accuracy: 0.9178
F1: 0.9155
Recall: 0.9178
Precision: 0.9138

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: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Precision
0.3342	1.0	268	0.3774	0.8497	0.8702	0.8497	0.9131
0.2411	2.0	536	0.4330	0.9020	0.9097	0.9020	0.9237
0.1374	3.0	804	0.5690	0.8964	0.9050	0.8964	0.9206
0.0804	4.0	1072	1.0798	0.9188	0.9140	0.9188	0.9117
0.0428	5.0	1340	1.0451	0.9178	0.9155	0.9178	0.9138

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

Esmail275/distilbert-base-uncased-finetuned_on_hata_dateset

distilbert-base-uncased-finetuned_on_hata_dateset

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Esmail275/
distilbert-base-uncased-finetuned_on_hata_dateset