--- base_model: facebook/roberta-hate-speech-dynabench-r4-target tags: - generated_from_trainer metrics: - accuracy model-index: - name: experiment-model-roberta results: [] --- # experiment-model-roberta This model is a fine-tuned version of [facebook/roberta-hate-speech-dynabench-r4-target](https://huggingface.co./facebook/roberta-hate-speech-dynabench-r4-target) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6733 - Accuracy: 0.8538 ## 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: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3299 | 1.0 | 884 | 0.3470 | 0.8453 | | 0.3061 | 2.0 | 1768 | 0.3472 | 0.8546 | | 0.2706 | 3.0 | 2652 | 0.3926 | 0.8583 | | 0.1706 | 4.0 | 3536 | 0.5401 | 0.8495 | | 0.1454 | 5.0 | 4420 | 0.6733 | 0.8538 | ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2