---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- wmt20_mlqe_task1
model-index:
- name: xlmr-ne-en-train_shuffled-1986-test2000
  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-ne-en-train_shuffled-1986-test2000

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: 0.5106
- R Squared: 0.2714
- Mae: 0.5502
- Pearson R: 0.6939

## 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  | 0.4648          | 0.3368    | 0.5563 | 0.6413    |
| 0.7538        | 2.0   | 750  | 0.3918          | 0.4409    | 0.4969 | 0.6785    |
| 0.5265        | 3.0   | 1125 | 0.5106          | 0.2714    | 0.5502 | 0.6939    |


### Framework versions

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