readme: ---
  license: mit
  tags:
  - generated_from_trainer
  - nlu
  - intent-classification
  metrics:
  - accuracy
  - f1
  model-index:
  - name: xlm-r-base-amazon-massive-intent
    results:
    - task:
        name: intent-classification
        type: intent-classification
      dataset:
        name: MASSIVE
        type: AmazonScience/massive
        split: test
      metrics:
      - name: F1
        type: f1
        value: 0.8775
  datasets:
  - AmazonScience/massive
  language:
  - en
  ---
  
  <!-- 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. -->
  
  # xlm-r-base-amazon-massive-intent
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on 
  [Amazon Massive](https://huggingface.co/datasets/AmazonScience/massive) dataset (only en-US subset).
  It achieves the following results on the evaluation set:
  - Loss: 0.5439
  - Accuracy: 0.8775
  - F1: 0.8775
  
  ## Results
  
  | domain | train-accuracy | test-accuracy |
  |:------:|:--------------:|:-------------:|
  |alarm|0.967|0.9846|
  |audio|0.7458|0.659|
  |calendar|0.9797|0.3181|
  |cooking|0.9714|0.9571|
  |datetime|0.9777|0.9402|
  |email|0.9727|0.9296|
  |general|0.8952|0.5949|
  |iot|0.9329|0.9122|
  |list|0.9792|0.9538|
  |music|0.9355|0.8837|
  |news|0.9607|0.8764|
  |play|0.9419|0.874|
  |qa|0.9677|0.8591|
  |recommendation|0.9515|0.8764|
  |social|0.9671|0.8932|
  |takeaway|0.9192|0.8478|
  |transport|0.9425|0.9193|
  |weather|0.9895|0.93|
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 2.734         | 1.0   | 720  | 1.1883          | 0.7196   | 0.7196 |
  | 1.2774        | 2.0   | 1440 | 0.7162          | 0.8342   | 0.8342 |
  | 0.6301        | 3.0   | 2160 | 0.5817          | 0.8672   | 0.8672 |
  | 0.4901        | 4.0   | 2880 | 0.5555          | 0.8770   | 0.8770 |
  | 0.3398        | 5.0   | 3600 | 0.5439          | 0.8775   | 0.8775 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1