---
language:
- en
- de
- fr
- it
- pt
- es
- pl
license: mit
tags:
- generated_from_trainer
- nlu
- text-classification
datasets:
- AmazonScience/massive
metrics:
- accuracy
- f1
base_model: microsoft/Multilingual-MiniLM-L12-H384
model-index:
- name: multilingual_minilm-amazon_massive-intent_eu7
  results:
  - task:
      type: text-classification
      name: text-classification
    dataset:
      name: MASSIVE
      type: AmazonScience/massive
      split: test
    metrics:
    - type: f1
      value: 0.8623
      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_eu7

This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the [MASSIVE 1.1](https://huggingface.co/datasets/AmazonScience/massive) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8238
- Accuracy: 0.8623
- F1: 0.8623

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.3523        | 1.0   | 5038  | 1.3058          | 0.6937   | 0.6937 |
| 0.7842        | 2.0   | 10076 | 0.8434          | 0.8059   | 0.8059 |
| 0.5359        | 3.0   | 15114 | 0.7231          | 0.8302   | 0.8302 |
| 0.4106        | 4.0   | 20152 | 0.7121          | 0.8443   | 0.8443 |
| 0.3294        | 5.0   | 25190 | 0.7366          | 0.8497   | 0.8497 |
| 0.2621        | 6.0   | 30228 | 0.7702          | 0.8528   | 0.8528 |
| 0.2164        | 7.0   | 35266 | 0.7773          | 0.8577   | 0.8577 |
| 0.1756        | 8.0   | 40304 | 0.8080          | 0.8569   | 0.8569 |
| 0.1625        | 9.0   | 45342 | 0.8162          | 0.8624   | 0.8624 |
| 0.1448        | 10.0  | 50380 | 0.8238          | 0.8623   | 0.8623 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2