--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 base_model: xlm-roberta-base model-index: - name: xlm-roberta-base-finetuned-panx-de results: - task: type: token-classification name: Token Classification dataset: name: xtreme type: xtreme args: PAN-X.de metrics: - type: f1 value: 0.8683253805953192 name: F1 --- # 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: 0.1386 - F1: 0.8683 ## 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: 15 - eval_batch_size: 15 - 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 | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.2501 | 1.0 | 839 | 0.1879 | 0.8135 | | 0.1328 | 2.0 | 1678 | 0.1419 | 0.8475 | | 0.0792 | 3.0 | 2517 | 0.1386 | 0.8683 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.10.0 - Datasets 2.3.2 - Tokenizers 0.12.1