readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - wmt20_mlqe_task1
  model-index:
  - name: xlm-roberta-base-wmt20-qe-ro-en
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # xlm-roberta-base-wmt20-qe-ro-en
  
  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: 0.3299
  - R Squared: 0.6382
  - Mae: 0.4068
  - Pearson R: 0.8410
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | R Squared | Mae    | Pearson R |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---------:|
  | No log        | 1.0   | 438  | 0.3185          | 0.6507    | 0.4301 | 0.8138    |
  | 0.5963        | 2.0   | 876  | 0.3007          | 0.6703    | 0.4026 | 0.8402    |
  | 0.3414        | 3.0   | 1314 | 0.3299          | 0.6382    | 0.4068 | 0.8410    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.11.0+cu102
  - Datasets 2.8.0
  - Tokenizers 0.12.1
  