--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-de results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme config: PAN-X.de split: train args: PAN-X.de metrics: - name: F1 type: f1 value: 0.8743895513912551 --- # xlm-roberta-base-finetuned-panx-de This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. It achieves the following results on the evaluation set: - Loss: 0.1597 - F1: 0.8744 ## 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: 5e-05 - train_batch_size: 24 - eval_batch_size: 24 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.2589 | 1.0 | 525 | 0.1590 | 0.8195 | | 0.1322 | 2.0 | 1050 | 0.1578 | 0.8313 | | 0.093 | 3.0 | 1575 | 0.1501 | 0.8590 | | 0.0621 | 4.0 | 2100 | 0.1443 | 0.8682 | | 0.0401 | 5.0 | 2625 | 0.1597 | 0.8744 | ### Framework versions - Transformers 4.24.0 - Pytorch 1.12.1+cu113 - Datasets 2.6.1 - Tokenizers 0.13.2