--- license: mit base_model: numind/NuNER-v2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: nuner-v2_fewnerd_fine_super results: [] --- # nuner-v2_fewnerd_fine_super This model is a fine-tuned version of [numind/NuNER-v2.0](https://huggingface.co/numind/NuNER-v2.0) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2362 - Precision: 0.6810 - Recall: 0.7160 - F1: 0.6981 - Accuracy: 0.9313 ## 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: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.2602 | 1.0 | 2059 | 0.2486 | 0.6570 | 0.7031 | 0.6793 | 0.9270 | | 0.2199 | 2.0 | 4118 | 0.2369 | 0.6791 | 0.7043 | 0.6915 | 0.9302 | | 0.2052 | 3.0 | 6177 | 0.2349 | 0.6785 | 0.7143 | 0.6959 | 0.9312 | | 0.1835 | 4.0 | 8236 | 0.2362 | 0.6810 | 0.7160 | 0.6981 | 0.9313 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2