distilbert-base-uncased__hate_speech_offensive__train-16-2

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: 0.9210
• Accuracy: 0.5635

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
1.0915	1.0	10	1.1051	0.4
1.0663	2.0	20	1.0794	0.3
1.0307	3.0	30	1.0664	0.5
0.9443	4.0	40	1.0729	0.5
0.8373	5.0	50	1.0175	0.4
0.6892	6.0	60	0.9624	0.5
0.538	7.0	70	0.9924	0.5
0.4173	8.0	80	1.0136	0.6
0.1846	9.0	90	1.0683	0.6
0.1125	10.0	100	1.2376	0.6
0.0754	11.0	110	1.2537	0.6
0.0401	12.0	120	1.4387	0.6
0.0285	13.0	130	1.5702	0.6
0.0241	14.0	140	1.6795	0.6
0.0175	15.0	150	1.7228	0.6
0.0147	16.0	160	1.7892	0.6

Framework versions

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