--- license: apache-2.0 tags: - generated_from_trainer metrics: - f1 - accuracy - precision - recall model-index: - name: bert-bert-cased-first512-Conflict results: [] --- # bert-bert-cased-first512-Conflict `conv_text = '\n'.join([utt.text for utt in conv.get_chronological_utterance_list()])` This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6932 - F1: 0.6667 - Accuracy: 0.5 - Precision: 0.5 - Recall: 1.0 ## 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-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - 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 | F1 | Accuracy | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:| | 0.7098 | 1.0 | 685 | 0.6945 | 0.0 | 0.5 | 0.0 | 0.0 | | 0.7046 | 2.0 | 1370 | 0.6997 | 0.6667 | 0.5 | 0.5 | 1.0 | | 0.7013 | 3.0 | 2055 | 0.6949 | 0.6667 | 0.5 | 0.5 | 1.0 | | 0.7027 | 4.0 | 2740 | 0.6931 | 0.6667 | 0.5 | 0.5 | 1.0 | | 0.702 | 5.0 | 3425 | 0.6932 | 0.6667 | 0.5 | 0.5 | 1.0 | ### Framework versions - Transformers 4.18.0 - Pytorch 1.10.0+cu111 - Datasets 2.1.0 - Tokenizers 0.12.1