distilbert-base-uncased__hate_speech_offensive__train-16-4

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: 1.0903
• Accuracy: 0.4805

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
1.0974	1.0	10	1.1139	0.1
1.0637	2.0	20	1.0988	0.1
0.9758	3.0	30	1.1013	0.1
0.9012	4.0	40	1.0769	0.3
0.6993	5.0	50	1.0484	0.6
0.5676	6.0	60	1.0223	0.6
0.4069	7.0	70	0.9190	0.6
0.3192	8.0	80	1.1370	0.6
0.1112	9.0	90	1.1728	0.6
0.07	10.0	100	1.1998	0.6
0.0397	11.0	110	1.3700	0.6
0.027	12.0	120	1.3329	0.6
0.021	13.0	130	1.2697	0.6
0.0177	14.0	140	1.4195	0.6
0.0142	15.0	150	1.5342	0.6
0.0118	16.0	160	1.5999	0.6
0.0108	17.0	170	1.6327	0.6

Framework versions

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