--- library_name: transformers license: apache-2.0 base_model: answerdotai/ModernBert-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: assignment4_ModernBertBase_distilled_clinc results: [] --- # assignment4_ModernBertBase_distilled_clinc 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: 0.2197 - Accuracy: 0.9442 ## 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: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 318 | 0.4283 | 0.8984 | | 1.1736 | 2.0 | 636 | 0.2833 | 0.9319 | | 1.1736 | 3.0 | 954 | 0.2288 | 0.9445 | | 0.048 | 4.0 | 1272 | 0.2198 | 0.9435 | | 0.0048 | 5.0 | 1590 | 0.2197 | 0.9442 | ### Framework versions - Transformers 4.57.1 - Pytorch 2.8.0+cu126 - Datasets 4.0.0 - Tokenizers 0.22.1