|
--- |
|
language: |
|
- en |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
- nlu |
|
- intent-classification |
|
datasets: |
|
- AmazonScience/massive |
|
metrics: |
|
- accuracy |
|
- f1 |
|
base_model: xlm-roberta-base |
|
model-index: |
|
- name: xlm-r-base-amazon-massive-intent |
|
results: |
|
- task: |
|
type: intent-classification |
|
name: intent-classification |
|
dataset: |
|
name: MASSIVE |
|
type: AmazonScience/massive |
|
split: test |
|
metrics: |
|
- type: f1 |
|
value: 0.8775 |
|
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-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 |
|
|
|
## Results |
|
|
|
| domain | train-accuracy | test-accuracy | |
|
|:------:|:--------------:|:-------------:| |
|
|alarm|0.967|0.9846| |
|
|audio|0.7458|0.659| |
|
|calendar|0.9797|0.3181| |
|
|cooking|0.9714|0.9571| |
|
|datetime|0.9777|0.9402| |
|
|email|0.9727|0.9296| |
|
|general|0.8952|0.5949| |
|
|iot|0.9329|0.9122| |
|
|list|0.9792|0.9538| |
|
|music|0.9355|0.8837| |
|
|news|0.9607|0.8764| |
|
|play|0.9419|0.874| |
|
|qa|0.9677|0.8591| |
|
|recommendation|0.9515|0.8764| |
|
|social|0.9671|0.8932| |
|
|takeaway|0.9192|0.8478| |
|
|transport|0.9425|0.9193| |
|
|weather|0.9895|0.93| |
|
|
|
## 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 |
