--- library_name: transformers license: apache-2.0 base_model: answerdotai/ModernBERT-base tags: - generated_from_trainer metrics: - f1 - accuracy - precision - recall model-index: - name: fluency-scorer results: [] --- # fluency-scorer This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5555 - F1: 0.6007 - Accuracy: 0.696 - Precision: 0.6271 - Recall: 0.696 ## 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: 3e-05 - train_batch_size: 128 - eval_batch_size: 128 - seed: 42 - optimizer: Use OptimizerNames.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_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:| | No log | 0 | 0 | 0.8275 | 0.2749 | 0.336 | 0.5265 | 0.336 | | No log | 1.0 | 8 | 0.6056 | 0.6355 | 0.669 | 0.6265 | 0.669 | | 0.7136 | 2.0 | 16 | 0.5566 | 0.6004 | 0.693 | 0.6178 | 0.693 | | 0.5579 | 3.0 | 24 | 0.5555 | 0.6007 | 0.696 | 0.6271 | 0.696 | ### Framework versions - Transformers 4.48.1 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0