--- library_name: transformers license: apache-2.0 base_model: google-bert/bert-large-uncased tags: - generated_from_trainer metrics: - f1 - accuracy model-index: - name: CS221-bert-large-uncased-finetuned-semeval results: [] --- # CS221-bert-large-uncased-finetuned-semeval This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co./google-bert/bert-large-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3493 - F1: 0.7668 - Roc Auc: 0.8210 - Accuracy: 0.4765 ## 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: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| | 0.55 | 1.0 | 70 | 0.5378 | 0.4156 | 0.6228 | 0.1625 | | 0.3931 | 2.0 | 140 | 0.4018 | 0.6857 | 0.7636 | 0.3989 | | 0.2768 | 3.0 | 210 | 0.3776 | 0.7337 | 0.7972 | 0.4422 | | 0.2033 | 4.0 | 280 | 0.3493 | 0.7668 | 0.8210 | 0.4765 | | 0.1157 | 5.0 | 350 | 0.3954 | 0.7648 | 0.8254 | 0.4675 | | 0.0746 | 6.0 | 420 | 0.4089 | 0.7660 | 0.8235 | 0.4747 | | 0.0539 | 7.0 | 490 | 0.4444 | 0.7597 | 0.8170 | 0.4567 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0