--- library_name: transformers license: mit base_model: FacebookAI/xlm-roberta-base tags: - generated_from_trainer model-index: - name: tir-xlm-asym-lr-3e-5 results: [] --- # tir-xlm-asym-lr-3e-5 This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1185 - F1-micro: 0.3399 - F1-macro: 0.1767 ## 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: 3e-05 - train_batch_size: 16 - eval_batch_size: 8 - 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: linear - lr_scheduler_warmup_steps: 73 - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1-micro | F1-macro | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| | 0.1209 | 1.0 | 184 | 0.1187 | 0.3399 | 0.1767 | | 0.1197 | 2.0 | 368 | 0.1186 | 0.3399 | 0.1767 | | 0.1195 | 3.0 | 552 | 0.1185 | 0.3399 | 0.1767 | | 0.1194 | 4.0 | 736 | 0.1185 | 0.3399 | 0.1767 | ### Framework versions - Transformers 4.48.1 - Pytorch 2.4.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0