Hate-Speech-Detection-mpnet-basev2
This model is a fine-tuned version of sentence-transformers/all-mpnet-base-v2 on the tweets_hate_speech_detection dataset. It achieves the following results on the evaluation set:
- Loss: 0.0849
- Accuracy: 0.9750
- F1: 0.8030
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.1144 | 1.0 | 1599 | 0.0955 | 0.9693 | 0.7337 |
0.072 | 2.0 | 3198 | 0.0849 | 0.9750 | 0.8030 |
0.0458 | 3.0 | 4797 | 0.0841 | 0.9764 | 0.8011 |
0.0156 | 4.0 | 6396 | 0.1829 | 0.9689 | 0.7762 |
0.012 | 5.0 | 7995 | 0.1904 | 0.9745 | 0.7758 |
0.0157 | 6.0 | 9594 | 0.1622 | 0.9758 | 0.7914 |
0.0068 | 7.0 | 11193 | 0.1741 | 0.9736 | 0.8005 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1
- Datasets 2.10.1
- Tokenizers 0.13.3
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Dataset used to train Arvnd03/Hate-Speech-Detection-mpnet-basev2
Evaluation results
- Accuracy on tweets_hate_speech_detectionself-reported0.975
- F1 on tweets_hate_speech_detectionself-reported0.803