--- library_name: transformers license: mit base_model: FacebookAI/xlm-roberta-large tags: - generated_from_trainer metrics: - f1 model-index: - name: xlm-roberta-large-sdg-classification results: [] datasets: - albertmartinez/OSDG pipeline_tag: text-classification --- # xlm-roberta-large-sdg-classification This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6536 - F1: 0.8114 ## 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: 1e-05 - train_batch_size: 64 - eval_batch_size: 64 - 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: 600 - num_epochs: 5.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | F1 | Validation Loss | |:-------------:|:-----:|:----:|:------:|:---------------:| | 1.7444 | 1.0 | 538 | 0.7686 | 0.8148 | | 0.7749 | 2.0 | 1076 | 0.8000 | 0.7104 | | 0.6165 | 3.0 | 1614 | 0.8114 | 0.6536 | | 0.5044 | 4.0 | 2152 | 0.8140 | 0.6571 | | 0.4217 | 5.0 | 2690 | 0.8154 | 0.6651 | ### Framework versions - Transformers 4.49.0.dev0 - Pytorch 2.1.2.post304 - Datasets 3.2.0 - Tokenizers 0.21.0