--- license: mit tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: roberta-finetuned-WebClassification-v2-smalllinguaENv2 results: [] --- # roberta-finetuned-WebClassification-v2-smalllinguaENv2 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: 1.7384 - Accuracy: 0.55 - F1: 0.55 - Precision: 0.55 - Recall: 0.55 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | No log | 1.0 | 20 | 2.9187 | 0.075 | 0.075 | 0.075 | 0.075 | | No log | 2.0 | 40 | 2.8030 | 0.15 | 0.15 | 0.15 | 0.15 | | No log | 3.0 | 60 | 2.6273 | 0.325 | 0.325 | 0.325 | 0.325 | | No log | 4.0 | 80 | 2.3371 | 0.45 | 0.45 | 0.45 | 0.45 | | No log | 5.0 | 100 | 2.1233 | 0.425 | 0.425 | 0.425 | 0.425 | | No log | 6.0 | 120 | 1.9737 | 0.525 | 0.525 | 0.525 | 0.525 | | No log | 7.0 | 140 | 1.8962 | 0.475 | 0.4750 | 0.475 | 0.475 | | No log | 8.0 | 160 | 1.8013 | 0.525 | 0.525 | 0.525 | 0.525 | | No log | 9.0 | 180 | 1.7384 | 0.55 | 0.55 | 0.55 | 0.55 | | No log | 10.0 | 200 | 1.7237 | 0.55 | 0.55 | 0.55 | 0.55 | ### Framework versions - Transformers 4.31.0.dev0 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.13.3