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---
language:
- en
license: mit
tags:
- generated_from_trainer
- nlu
- intent-classification
datasets:
- AmazonScience/massive
metrics:
- accuracy
- f1
pipeline_tag: text-classification
base_model: microsoft/Multilingual-MiniLM-L12-H384
model-index:
- name: multilingual_minilm-amazon-massive-intent
results:
- task:
type: intent-classification
name: intent-classification
dataset:
name: MASSIVE
type: AmazonScience/massive
split: test
metrics:
- type: f1
value: 0.8234
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. -->
# multilingual_minilm-amazon-massive-intent
This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the [MASSIVE1.1](https://huggingface.co/datasets/AmazonScience/massive) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8941
- Accuracy: 0.8234
- F1: 0.8234
## 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 3.7961 | 1.0 | 720 | 3.1657 | 0.3404 | 0.3404 |
| 3.1859 | 2.0 | 1440 | 2.4835 | 0.4343 | 0.4343 |
| 2.3104 | 3.0 | 2160 | 2.0474 | 0.5652 | 0.5652 |
| 2.0071 | 4.0 | 2880 | 1.7190 | 0.6503 | 0.6503 |
| 1.5595 | 5.0 | 3600 | 1.4873 | 0.6990 | 0.6990 |
| 1.3664 | 6.0 | 4320 | 1.3088 | 0.7354 | 0.7354 |
| 1.1272 | 7.0 | 5040 | 1.1964 | 0.7521 | 0.7521 |
| 1.0128 | 8.0 | 5760 | 1.1115 | 0.7718 | 0.7718 |
| 0.9405 | 9.0 | 6480 | 1.0598 | 0.7841 | 0.7841 |
| 0.7758 | 10.0 | 7200 | 1.0003 | 0.7944 | 0.7944 |
| 0.7457 | 11.0 | 7920 | 0.9599 | 0.8037 | 0.8037 |
| 0.6605 | 12.0 | 8640 | 0.9175 | 0.8165 | 0.8165 |
| 0.6135 | 13.0 | 9360 | 0.9148 | 0.8190 | 0.8190 |
| 0.5698 | 14.0 | 10080 | 0.8976 | 0.8229 | 0.8229 |
| 0.5578 | 15.0 | 10800 | 0.8941 | 0.8234 | 0.8234 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2 |