xlmr-wmt20qe1-et-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: 0.5172
- R Squared: 0.3115
- Mae: 0.5282
- Pearson R: 0.6791
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 | 0.5029 | 0.3306 | 0.5891 | 0.6394 |
| 0.7331 | 2.0 | 750 | 0.4183 | 0.4432 | 0.4958 | 0.6849 |
| 0.5087 | 3.0 | 1125 | 0.5172 | 0.3115 | 0.5282 | 0.6791 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
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