--- license: mit tags: - generated_from_trainer metrics: - f1 model-index: - name: DIPROMATS_subtask_1_base_train results: [] --- # DIPROMATS_subtask_1_base_train This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5120 - F1: 0.8267 ## 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: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.4533 | 1.0 | 182 | 0.3471 | 0.7932 | | 0.1763 | 2.0 | 364 | 0.3473 | 0.8116 | | 0.1359 | 3.0 | 546 | 0.3887 | 0.8144 | | 0.1728 | 4.0 | 728 | 0.4311 | 0.8147 | | 0.1519 | 5.0 | 910 | 0.4881 | 0.8236 | | 0.0085 | 6.0 | 1092 | 0.5120 | 0.8267 | | 0.1828 | 7.0 | 1274 | 0.5591 | 0.8118 | | 0.0071 | 8.0 | 1456 | 0.6079 | 0.8263 | | 0.0015 | 9.0 | 1638 | 0.6919 | 0.8235 | | 0.0241 | 10.0 | 1820 | 0.6990 | 0.8221 | ### Framework versions - Transformers 4.28.1 - Pytorch 1.13.1 - Datasets 2.12.0 - Tokenizers 0.13.3