--- license: mit base_model: xlm-roberta-base tags: - generated_from_trainer datasets: - wmt20_mlqe_task1 model-index: - name: xlmr-si-en-no_shuffled-orig-test1000 results: [] --- # xlmr-si-en-no_shuffled-orig-test1000 This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co./xlm-roberta-base) on the wmt20_mlqe_task1 dataset. It achieves the following results on the evaluation set: - Loss: 0.6696 - R Squared: -0.0587 - Mae: 0.6388 - Pearson R: 0.5256 ## 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: 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 | R Squared | Mae | Pearson R | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---------:| | No log | 1.0 | 438 | 0.5300 | 0.1620 | 0.6148 | 0.4337 | | 0.8691 | 2.0 | 876 | 0.4828 | 0.2366 | 0.5737 | 0.5227 | | 0.7034 | 3.0 | 1314 | 0.7226 | -0.1425 | 0.6706 | 0.5349 | | 0.539 | 4.0 | 1752 | 0.6373 | -0.0077 | 0.6250 | 0.5361 | | 0.3837 | 5.0 | 2190 | 0.6696 | -0.0587 | 0.6388 | 0.5256 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.0.1+cu117 - Datasets 2.14.6 - Tokenizers 0.14.1