readme: ---
  license: mit
  tags:
  - generated_from_trainer
  - nlu
  - text-classification
  metrics:
  - accuracy
  - f1
  model-index:
  - name: multilingual_minilm-amazon_massive-intent_eu7
    results:
    - task: 
        name: text-classification
        type: text-classification  
      dataset:
        name: MASSIVE
        type: AmazonScience/massive
        split: test
      metrics:
        - name: F1
          type: f1
          value: 0.8623
  datasets:
  - AmazonScience/massive
  language:
  - en
  - 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_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