--- license: apache-2.0 base_model: bert-large-uncased tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: bert-large-uncased-detect-dep-v9 results: [] --- # bert-large-uncased-detect-dep-v9 This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5392 - Accuracy: 0.734 - F1: 0.8150 ## 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: 5e-06 - train_batch_size: 12 - eval_batch_size: 12 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.637 | 1.0 | 501 | 0.5618 | 0.704 | 0.8 | | 0.6183 | 2.0 | 1002 | 0.5491 | 0.717 | 0.8068 | | 0.6042 | 3.0 | 1503 | 0.5392 | 0.734 | 0.8150 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.0 - Tokenizers 0.13.3