readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: distilbert-base-uncased-finetuned-switchboard-2
    results: []
  ---
  
  <!-- 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. -->
  
  # distilbert-base-uncased-finetuned-switchboard-2
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on Switchboard dataset.
  It achieves the following results on the validation set:
  - Loss: 0.7090
  - Accuracy: 0.7215
  - Precision: 0.7176
  - Recall: 0.7215
  - F1: 0.7188
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.2139        | 1.0   | 370  | 0.8510          | 0.6875   | 0.6831    | 0.6875 | 0.6846 |
  | 0.3195        | 2.0   | 740  | 0.7090          | 0.7215   | 0.7176    | 0.7215 | 0.7188 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.13.0+cu116
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  