--- license: mit tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: xlm-r-base-amazon-massive-domain results: [] datasets: - AmazonScience/massive language: - en --- # xlm-r-base-amazon-massive-domain This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the [Amazon Massive](https://huggingface.co/datasets/AmazonScience/massive) dataset (only en-US subset). It achieves the following results on the evaluation set: - Loss: 0.3788 - Accuracy: 0.9213 - F1: 0.9213 ## Model description Domain classifier trained from Amazon Massive dataset. ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 1.382 | 1.0 | 720 | 0.4533 | 0.8795 | 0.8795 | | 0.4598 | 2.0 | 1440 | 0.3448 | 0.9026 | 0.9026 | | 0.2547 | 3.0 | 2160 | 0.3762 | 0.9065 | 0.9065 | | 0.1986 | 4.0 | 2880 | 0.3748 | 0.9139 | 0.9139 | | 0.1358 | 5.0 | 3600 | 0.3788 | 0.9213 | 0.9213 | ### Framework versions - Transformers 4.22.1 - Pytorch 1.12.1+cu113 - Datasets 2.5.1 - Tokenizers 0.12.1