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---
language:
- en
license: mit
tags:
- generated_from_trainer
- nlu
- domain-classificatoin
- 'arxiv: 2310.16609'
datasets:
- AmazonScience/massive
metrics:
- accuracy
- f1
base_model: xlm-roberta-base
model-index:
- name: xlm-r-base-amazon-massive-domain
results:
- task:
type: text-classification
name: text-classification
dataset:
name: MASSIVE
type: AmazonScience/massive
split: test
metrics:
- type: f1
value: 0.9213
name: F1
---
<!-- 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. -->
# xlm-r-base-amazon-massive-domain
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the [Amazon Massive](https://huggingface.co/datasets/AmazonScience/massive) dataset (only en-US subset).
It achieves the following results on the evaluation set:
- Loss: 0.3788
- Accuracy: 0.9213
- F1: 0.9213
## Model description
Domain classifier trained from Amazon Massive dataset.
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.382 | 1.0 | 720 | 0.4533 | 0.8795 | 0.8795 |
| 0.4598 | 2.0 | 1440 | 0.3448 | 0.9026 | 0.9026 |
| 0.2547 | 3.0 | 2160 | 0.3762 | 0.9065 | 0.9065 |
| 0.1986 | 4.0 | 2880 | 0.3748 | 0.9139 | 0.9139 |
| 0.1358 | 5.0 | 3600 | 0.3788 | 0.9213 | 0.9213 |
### Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
## Citation
```bibtex
@article{kubis2023back,
title={Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition Errors},
author={Kubis, Marek and Sk{\'o}rzewski, Pawe{\l} and Sowa{\'n}ski, Marcin and Zi{\k{e}}tkiewicz, Tomasz},
journal={arXiv preprint arXiv:2310.16609},
year={2023}
eprint={2310.16609},
archivePrefix={arXiv},
}
``` |