---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: slurp-intent_baseline-xlm_r-en
  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. -->

# slurp-intent_baseline-xlm_r-en

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an SLURP dataset.

It achieves the following results on the test set:
- Loss: 0.68222
- Accuracy: 0.8746
- F1: 0.8746

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.9687        | 1.0   | 720  | 1.3267          | 0.6955   | 0.6955 |
| 1.4534        | 2.0   | 1440 | 0.8053          | 0.8219   | 0.8219 |
| 0.6775        | 3.0   | 2160 | 0.6912          | 0.8421   | 0.8421 |
| 0.5624        | 4.0   | 2880 | 0.6377          | 0.8623   | 0.8623 |
| 0.3756        | 5.0   | 3600 | 0.6188          | 0.8746   | 0.8746 |
| 0.3346        | 6.0   | 4320 | 0.6548          | 0.8711   | 0.8711 |
| 0.2541        | 7.0   | 5040 | 0.6618          | 0.8751   | 0.8751 |
| 0.2243        | 8.0   | 5760 | 0.6662          | 0.8780   | 0.8780 |
| 0.212         | 9.0   | 6480 | 0.6673          | 0.8810   | 0.8810 |
| 0.1664        | 10.0  | 7200 | 0.6783          | 0.8810   | 0.8810 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3