distilbert-base-uncased__hate_speech_offensive__train-8-5

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: 1.7214
• Accuracy: 0.37

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
1.0995	1.0	5	1.1301	0.0
1.0227	2.0	10	1.1727	0.0
1.0337	3.0	15	1.1734	0.2
0.9137	4.0	20	1.1829	0.2
0.8065	5.0	25	1.1496	0.4
0.7038	6.0	30	1.1101	0.4
0.6246	7.0	35	1.0982	0.2
0.4481	8.0	40	1.0913	0.2
0.3696	9.0	45	1.0585	0.4
0.3137	10.0	50	1.0418	0.4
0.2482	11.0	55	1.0078	0.4
0.196	12.0	60	0.9887	0.6
0.1344	13.0	65	0.9719	0.6
0.1014	14.0	70	1.0053	0.6
0.111	15.0	75	0.9653	0.6
0.0643	16.0	80	0.9018	0.6
0.0559	17.0	85	0.9393	0.6
0.0412	18.0	90	1.0210	0.6
0.0465	19.0	95	0.9965	0.6
0.0328	20.0	100	0.9739	0.6
0.0289	21.0	105	0.9796	0.6
0.0271	22.0	110	0.9968	0.6
0.0239	23.0	115	1.0143	0.6
0.0201	24.0	120	1.0459	0.6
0.0185	25.0	125	1.0698	0.6
0.0183	26.0	130	1.0970	0.6

Framework versions

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