distilbert-base-uncased__hate_speech_offensive__train-8-3

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: 0.9681
• Accuracy: 0.549

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
1.1073	1.0	5	1.1393	0.0
1.0392	2.0	10	1.1729	0.0
1.0302	3.0	15	1.1694	0.2
0.9176	4.0	20	1.1846	0.2
0.8339	5.0	25	1.1663	0.2
0.7533	6.0	30	1.1513	0.4
0.6327	7.0	35	1.1474	0.4
0.4402	8.0	40	1.1385	0.4
0.3752	9.0	45	1.0965	0.2
0.3448	10.0	50	1.0357	0.2
0.2582	11.0	55	1.0438	0.2
0.1903	12.0	60	1.0561	0.2
0.1479	13.0	65	1.0569	0.2
0.1129	14.0	70	1.0455	0.2
0.1071	15.0	75	1.0416	0.4
0.0672	16.0	80	1.1164	0.4
0.0561	17.0	85	1.1846	0.6
0.0463	18.0	90	1.2040	0.6
0.0431	19.0	95	1.2078	0.6
0.0314	20.0	100	1.2368	0.6

Framework versions

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