--- license: mit tags: - generated_from_trainer datasets: - tweets_hate_speech_detection metrics: - accuracy - f1 model-index: - name: FirstTry results: - task: name: Text Classification type: text-classification dataset: name: tweets_hate_speech_detection type: tweets_hate_speech_detection config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.9821679962458939 - name: F1 type: f1 value: 0.8692660550458716 --- # FirstTry This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the tweets_hate_speech_detection dataset. It achieves the following results on the evaluation set: - Loss: 0.0847 - Accuracy: 0.9822 - F1: 0.8693 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.1159 | 1.0 | 1599 | 0.1019 | 0.9759 | 0.8270 | | 0.0727 | 2.0 | 3198 | 0.0965 | 0.9795 | 0.8424 | | 0.044 | 3.0 | 4797 | 0.0847 | 0.9822 | 0.8693 | | 0.0301 | 4.0 | 6396 | 0.1121 | 0.9811 | 0.8660 | | 0.0206 | 5.0 | 7995 | 0.1718 | 0.9700 | 0.8110 | | 0.0176 | 6.0 | 9594 | 0.1453 | 0.9811 | 0.8591 | ### Framework versions - Transformers 4.26.1 - Pytorch 2.0.1 - Datasets 2.10.1 - Tokenizers 0.13.3