distilbert-base-uncased__hate_speech_offensive__train-32-6

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.0523
• Accuracy: 0.663

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0957	1.0	19	1.0696	0.6
1.0107	2.0	38	1.0047	0.55
0.8257	3.0	57	0.8358	0.8
0.6006	4.0	76	0.7641	0.6
0.4172	5.0	95	0.5931	0.8
0.2639	6.0	114	0.5570	0.7
0.1314	7.0	133	0.5017	0.65
0.0503	8.0	152	0.3115	0.75
0.023	9.0	171	0.4353	0.85
0.0128	10.0	190	0.5461	0.75
0.0092	11.0	209	0.5045	0.8
0.007	12.0	228	0.5014	0.8
0.0064	13.0	247	0.5070	0.8
0.0049	14.0	266	0.4681	0.8
0.0044	15.0	285	0.4701	0.8
0.0039	16.0	304	0.4862	0.8
0.0036	17.0	323	0.4742	0.8
0.0035	18.0	342	0.4652	0.8

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.2+cu102
• Datasets 1.18.2
• Tokenizers 0.10.3