readme: ---
  license: mit
  tags:
  - generated_from_trainer
  - nlu
  - text-classification
  - intent-classification
  metrics:
  - accuracy
  - f1
  model-index:
  - name: multilingual_minilm-amazon_massive-intent_eu_noen
    results:
    - task:
        name: intent-classification
        type: intent-classification
      dataset:
        name: MASSIVE
        type: AmazonScience/massive
        split: test
      metrics:
      - name: F1
        type: f1
        value: 0.8551
  datasets:
  - AmazonScience/massive
  language:
  - de
  - fr
  - it
  - pt
  - es
  - pl
  ---
  
  <!-- 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_eu_noen
  
  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: 0.7794
  - 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