---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-r-base-amazon-massive-intent
  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. -->

# xlm-r-base-amazon-massive-intent

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on 
[Amazon Massive](https://huggingface.co/datasets/AmazonScience/massive) dataset (only en-US subset).
It achieves the following results on the evaluation set:
- Loss: 0.5439
- Accuracy: 0.8775
- F1: 0.8775

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.734         | 1.0   | 720  | 1.1883          | 0.7196   | 0.7196 |
| 1.2774        | 2.0   | 1440 | 0.7162          | 0.8342   | 0.8342 |
| 0.6301        | 3.0   | 2160 | 0.5817          | 0.8672   | 0.8672 |
| 0.4901        | 4.0   | 2880 | 0.5555          | 0.8770   | 0.8770 |
| 0.3398        | 5.0   | 3600 | 0.5439          | 0.8775   | 0.8775 |


### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1