--- library_name: transformers license: apache-2.0 base_model: answerdotai/ModernBERT-large tags: - generated_from_trainer metrics: - accuracy model-index: - name: ModernBERT-large-zeroshot-v2.0-2024-12-28-00-13 results: [] --- # ModernBERT-large-zeroshot-v2.0-2024-12-28-00-13 This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co./answerdotai/ModernBERT-large) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1803 - F1 Macro: 0.6624 - F1 Micro: 0.7304 - Accuracy Balanced: 0.6979 - Accuracy: 0.7304 - Precision Macro: 0.6899 - Recall Macro: 0.6979 - Precision Micro: 0.7304 - Recall Micro: 0.7304 ## 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: 9e-06 - train_batch_size: 16 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.06 - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro | |:-------------:|:------:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:| | 0.3865 | 1.0 | 33915 | 0.3321 | 0.8584 | 0.8704 | 0.8600 | 0.8704 | 0.8569 | 0.8600 | 0.8704 | 0.8704 | | 0.2456 | 2.0000 | 67828 | 0.4069 | 0.8600 | 0.8728 | 0.8590 | 0.8728 | 0.8610 | 0.8590 | 0.8728 | 0.8728 | ### Framework versions - Transformers 4.48.0.dev0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0