--- library_name: transformers license: mit base_model: FacebookAI/xlm-roberta-base tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: XLM_CITA results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # XLM_CITA This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5616 - Accuracy: 0.7705 - F1: 0.7698 ## 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: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine_with_restarts - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.6485 | 1.0 | 250 | 0.6020 | 0.6645 | 0.6490 | | 0.5652 | 2.0 | 500 | 0.5210 | 0.7395 | 0.7397 | | 0.5122 | 3.0 | 750 | 0.5111 | 0.7495 | 0.7496 | | 0.4661 | 4.0 | 1000 | 0.5370 | 0.7685 | 0.7684 | | 0.4244 | 5.0 | 1250 | 0.5206 | 0.7635 | 0.7636 | | 0.3942 | 6.0 | 1500 | 0.5299 | 0.762 | 0.7621 | | 0.3611 | 7.0 | 1750 | 0.5380 | 0.7695 | 0.7686 | | 0.3421 | 8.0 | 2000 | 0.5595 | 0.7745 | 0.7736 | | 0.3362 | 9.0 | 2250 | 0.5596 | 0.7715 | 0.7708 | | 0.3274 | 10.0 | 2500 | 0.5616 | 0.7705 | 0.7698 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.1.2 - Datasets 2.19.2 - Tokenizers 0.21.0