distilbert-base-uncased__hate_speech_offensive__train-32-4

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: 0.7384
• Accuracy: 0.724

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
1.1013	1.0	19	1.0733	0.55
1.0226	2.0	38	1.0064	0.65
0.8539	3.0	57	0.8758	0.75
0.584	4.0	76	0.6941	0.7
0.2813	5.0	95	0.5151	0.7
0.1122	6.0	114	0.4351	0.8
0.0432	7.0	133	0.4896	0.85
0.0199	8.0	152	0.5391	0.85
0.0126	9.0	171	0.5200	0.85
0.0085	10.0	190	0.5622	0.85
0.0069	11.0	209	0.5950	0.85
0.0058	12.0	228	0.6015	0.85
0.0053	13.0	247	0.6120	0.85
0.0042	14.0	266	0.6347	0.85
0.0039	15.0	285	0.6453	0.85
0.0034	16.0	304	0.6660	0.85

Framework versions

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