readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncased-finetuned-mic
    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-mic
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5640
  - Accuracy: 0.7809
  - F1: 0.8769
  
  ## 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: 2.740146306575944e-05
  - train_batch_size: 400
  - eval_batch_size: 400
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | No log        | 1.0   | 18   | 0.7080          | 0.7232   | 0.8394 |
  | No log        | 2.0   | 36   | 0.4768          | 0.8443   | 0.9156 |
  | No log        | 3.0   | 54   | 0.5714          | 0.7866   | 0.8806 |
  | No log        | 4.0   | 72   | 0.7035          | 0.7151   | 0.8339 |
  | No log        | 5.0   | 90   | 0.5640          | 0.7809   | 0.8769 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0.dev0
  - Pytorch 1.10.1
  - Datasets 2.0.0
  - Tokenizers 0.11.0
  