distilbert-base-uncased__hate_speech_offensive__train-16-8

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: 1.0704
• Accuracy: 0.394

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
1.1031	1.0	10	1.1286	0.1
1.0648	2.0	20	1.1157	0.3
0.9982	3.0	30	1.1412	0.2
0.9283	4.0	40	1.2053	0.2
0.7958	5.0	50	1.1466	0.2
0.6668	6.0	60	1.1783	0.3
0.5068	7.0	70	1.2992	0.3
0.3741	8.0	80	1.3483	0.3
0.1653	9.0	90	1.4533	0.2
0.0946	10.0	100	1.6292	0.2
0.0569	11.0	110	1.8381	0.2
0.0346	12.0	120	2.0781	0.2

Framework versions

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