---
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