--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-en results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme args: PAN-X.en metrics: - name: F1 type: f1 value: 0.6994475138121546 --- # xlm-roberta-base-finetuned-panx-en 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: 0.3848 - F1: 0.6994 ## 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: 16 - eval_batch_size: 16 - 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 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 1.0435 | 1.0 | 74 | 0.5169 | 0.5532 | | 0.4719 | 2.0 | 148 | 0.4224 | 0.6630 | | 0.3424 | 3.0 | 222 | 0.3848 | 0.6994 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1