metadata
language:
- de
- fr
- it
- pt
- es
- pl
license: mit
tags:
- generated_from_trainer
- nlu
- text-classification
- intent-classification
datasets:
- AmazonScience/massive
metrics:
- accuracy
- f1
base_model: microsoft/Multilingual-MiniLM-L12-H384
model-index:
- name: multilingual_minilm-amazon_massive-intent_eu_noen
results:
- task:
type: intent-classification
name: intent-classification
dataset:
name: MASSIVE
type: AmazonScience/massive
split: test
metrics:
- type: f1
value: 0.8551
name: F1
multilingual_minilm-amazon_massive-intent_eu_noen
This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on the MASSIVE1.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7794
- Accuracy: 0.8551
- F1: 0.8551
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 |
|---|---|---|---|---|---|
| 1.7624 | 1.0 | 4318 | 1.5462 | 0.6331 | 0.6331 |
| 0.9535 | 2.0 | 8636 | 0.9628 | 0.7698 | 0.7698 |
| 0.6849 | 3.0 | 12954 | 0.8034 | 0.8097 | 0.8097 |
| 0.5163 | 4.0 | 17272 | 0.7444 | 0.8290 | 0.8290 |
| 0.3973 | 5.0 | 21590 | 0.7346 | 0.8383 | 0.8383 |
| 0.331 | 6.0 | 25908 | 0.7369 | 0.8453 | 0.8453 |
| 0.2876 | 7.0 | 30226 | 0.7325 | 0.8510 | 0.8510 |
| 0.2319 | 8.0 | 34544 | 0.7726 | 0.8496 | 0.8496 |
| 0.2098 | 9.0 | 38862 | 0.7803 | 0.8543 | 0.8543 |
| 0.1863 | 10.0 | 43180 | 0.7794 | 0.8551 | 0.8551 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2