xlmr-et-en-no_shuffled-orig-test1000
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: 0.5476
- R Squared: 0.2710
- Mae: 0.5508
- Pearson R: 0.6399
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 | 0.4918 | 0.3453 | 0.5703 | 0.5987 |
| 0.7759 | 2.0 | 876 | 0.4742 | 0.3687 | 0.5147 | 0.6788 |
| 0.5858 | 3.0 | 1314 | 0.4901 | 0.3476 | 0.5239 | 0.6641 |
| 0.4156 | 4.0 | 1752 | 0.4853 | 0.3539 | 0.5293 | 0.6553 |
| 0.3151 | 5.0 | 2190 | 0.5476 | 0.2710 | 0.5508 | 0.6399 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
FacebookAI/xlm-roberta-base