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---
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 |