--- license: mit tags: - generated_from_trainer base_model: FacebookAI/xlm-roberta-large metrics: - accuracy model-index: - name: fine-tune-xlm-roberta-TOG-split-headline1 results: [] --- # fine-tune-xlm-roberta-TOG-split-headline1 This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0897 - Accuracy: 0.3828 ## 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: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 7 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.0816 | 1.0 | 27 | 1.0912 | 0.3828 | | 1.0823 | 2.0 | 54 | 1.0932 | 0.3828 | | 1.0858 | 3.0 | 81 | 1.0910 | 0.3828 | | 1.0814 | 4.0 | 108 | 1.0907 | 0.3828 | | 1.0885 | 5.0 | 135 | 1.1030 | 0.3828 | | 1.0839 | 6.0 | 162 | 1.0962 | 0.3828 | | 1.0898 | 7.0 | 189 | 1.0897 | 0.3828 | ### Framework versions - Transformers 4.40.2 - Pytorch 2.2.1+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1