readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - massive
  metrics:
  - accuracy
  model-index:
  - name: bert-base-Massive-intent
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: massive
        type: massive
        config: en-US
        split: train
        args: en-US
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8858829316281358
  ---
  
  <!-- 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. -->
  
  # bert-base-Massive-intent
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the massive dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6707
  - Accuracy: 0.8859
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 33
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.6844        | 1.0   | 720  | 0.7190          | 0.8387   |
  | 0.4713        | 2.0   | 1440 | 0.5449          | 0.8726   |
  | 0.2459        | 3.0   | 2160 | 0.5893          | 0.8790   |
  | 0.1469        | 4.0   | 2880 | 0.6631          | 0.8795   |
  | 0.0874        | 5.0   | 3600 | 0.6707          | 0.8859   |
  | 0.0507        | 6.0   | 4320 | 0.7189          | 0.8844   |
  | 0.0344        | 7.0   | 5040 | 0.7480          | 0.8854   |
  | 0.0225        | 8.0   | 5760 | 0.7956          | 0.8844   |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  