--- license: mit base_model: FacebookAI/xlm-roberta-base tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: xlm-roberta-base-ner results: [] --- # xlm-roberta-base-ner This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1821 - Precision: 0.7700 - Recall: 0.8331 - F1: 0.8003 - Accuracy: 0.9436 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.2183 | 1.0 | 2078 | 0.2050 | 0.7135 | 0.8089 | 0.7582 | 0.9323 | | 0.1742 | 2.0 | 4156 | 0.1773 | 0.7461 | 0.8318 | 0.7866 | 0.9422 | | 0.1407 | 3.0 | 6234 | 0.1821 | 0.7700 | 0.8331 | 0.8003 | 0.9436 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1