distilbert-base-uncased__hate_speech_offensive__train-8-6

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: 1.1275
• Accuracy: 0.3795

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
1.11	1.0	5	1.1184	0.0
1.0608	2.0	10	1.1227	0.0
1.0484	3.0	15	1.1009	0.2
0.9614	4.0	20	1.1009	0.2
0.8545	5.0	25	1.0772	0.2
0.8241	6.0	30	1.0457	0.2
0.708	7.0	35	1.0301	0.4
0.5045	8.0	40	1.0325	0.4
0.4175	9.0	45	1.0051	0.4
0.3446	10.0	50	0.9610	0.4
0.2851	11.0	55	0.9954	0.4
0.1808	12.0	60	1.0561	0.4
0.1435	13.0	65	1.0218	0.4
0.1019	14.0	70	1.0254	0.4
0.0908	15.0	75	0.9935	0.4
0.0591	16.0	80	1.0090	0.4
0.0512	17.0	85	1.0884	0.4
0.0397	18.0	90	1.2732	0.4
0.039	19.0	95	1.2979	0.6
0.0325	20.0	100	1.2705	0.4

Framework versions

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