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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- wmt20_mlqe_task1
model-index:
- name: xlmr-en-de-no_shuffled-orig-test1000
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. -->
# xlmr-en-de-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: 0.5090
- R Squared: 0.0865
- Mae: 0.5291
- Pearson R: 0.3627
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | R Squared | Mae | Pearson R |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---------:|
| No log | 1.0 | 438 | 0.5544 | 0.0051 | 0.5990 | 0.3021 |
| 0.6821 | 2.0 | 876 | 0.5527 | 0.0082 | 0.5998 | 0.1601 |
| 0.7102 | 3.0 | 1314 | 0.5400 | 0.0309 | 0.5712 | 0.3027 |
| 0.7194 | 4.0 | 1752 | 0.5132 | 0.0791 | 0.5401 | 0.3557 |
| 0.6285 | 5.0 | 2190 | 0.5090 | 0.0865 | 0.5291 | 0.3627 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
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