--- library_name: transformers license: apache-2.0 base_model: answerdotai/ModernBERT-large tags: - generated_from_trainer model-index: - name: ModernBERT-large-ft-fineweb-edu-annotations results: [] --- # ModernBERT-large-ft-fineweb-edu-annotations This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1702 - F1 Score: 0.7571 - Precision Score: 0.7609 - Recall Score: 0.7554 ## 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: 8e-05 - train_batch_size: 24 - eval_batch_size: 24 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 Score | Precision Score | Recall Score | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------:| | 0.643 | 1.0 | 15581 | 0.5972 | 0.7481 | 0.7521 | 0.7463 | | 0.4219 | 2.0 | 31162 | 0.5946 | 0.7729 | 0.7846 | 0.7680 | | 0.1447 | 3.0 | 46743 | 1.1702 | 0.7571 | 0.7609 | 0.7554 | ### Framework versions - Transformers 4.48.0.dev0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0