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xlmr-si-en-train_shuffled-1986-test2000

This model is a fine-tuned version of xlm-roberta-base on the wmt20_mlqe_task1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5958
  • R Squared: 0.0579
  • Mae: 0.6098
  • Pearson R: 0.5648

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: 1986
  • 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 1.0 375 0.5272 0.1665 0.5927 0.5149
0.802 2.0 750 0.5288 0.1638 0.5966 0.5410
0.6144 3.0 1125 0.5958 0.0579 0.6098 0.5648

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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