distilbert-base-uncased__hate_speech_offensive__train-8-8

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: 1.0005
• Accuracy: 0.518

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
1.1029	1.0	5	1.1295	0.0
1.0472	2.0	10	1.1531	0.0
1.054	3.0	15	1.1475	0.0
0.9366	4.0	20	1.1515	0.0
0.8698	5.0	25	1.1236	0.4
0.8148	6.0	30	1.0716	0.6
0.6884	7.0	35	1.0662	0.6
0.5641	8.0	40	1.0671	0.6
0.5	9.0	45	1.0282	0.6
0.3882	10.0	50	1.0500	0.6
0.3522	11.0	55	1.1381	0.6
0.2492	12.0	60	1.1278	0.6
0.2063	13.0	65	1.0731	0.6
0.1608	14.0	70	1.1339	0.6
0.1448	15.0	75	1.1892	0.6
0.0925	16.0	80	1.1840	0.6
0.0768	17.0	85	1.0608	0.6
0.0585	18.0	90	1.1073	0.6
0.0592	19.0	95	1.3134	0.6

Framework versions

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