This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0996
F1: 0.9861
Accuracy: 0.9844

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: 1e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.6264	1.0	643	0.6426	0.8423	0.8179
0.7407	2.0	1286	0.4516	0.9121	0.9019
0.5953	3.0	1929	0.2944	0.9492	0.9416
0.3275	4.0	2572	0.3128	0.9522	0.9447
0.3185	5.0	3215	0.1861	0.9732	0.9696
0.1702	6.0	3858	0.1225	0.9818	0.9798
0.1411	7.0	4501	0.1027	0.9854	0.9837
0.0895	8.0	5144	0.0996	0.9861	0.9844

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

leofn3/modelo_racismo_13_dez

modelo_racismo_13_dez

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

leofn3/
modelo_racismo_13_dez