---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlmr-si-en-all_shuffled-42-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-si-en-all_shuffled-42-test1000

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co./xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8606
- R Squared: -0.0217
- Mae: 0.7408
- Pearson R: 0.5130

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | R Squared | Mae    | Pearson R |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---------:|
| No log        | 1.0   | 438  | 0.6977          | 0.1718    | 0.7326 | 0.4475    |
| 0.7872        | 2.0   | 876  | 0.6551          | 0.2223    | 0.6841 | 0.5166    |
| 0.6178        | 3.0   | 1314 | 0.8606          | -0.0217   | 0.7408 | 0.5130    |


### Framework versions

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