readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncased_finetuned_Balance_Upsampling_SPEECH_TEXT_DISPLAY_v1
    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_Balance_Upsampling_SPEECH_TEXT_DISPLAY_v1
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.6982
  - Accuracy: 0.7759
  - F1: 0.7743
  
  ## 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: 4
  - eval_batch_size: 4
  - 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 0.5321        | 1.0   | 7958  | 1.3225          | 0.7271   | 0.7391 |
  | 0.2967        | 2.0   | 15916 | 1.3868          | 0.7574   | 0.7601 |
  | 0.1821        | 3.0   | 23874 | 1.4753          | 0.7513   | 0.7515 |
  | 0.1193        | 4.0   | 31832 | 1.7028          | 0.7588   | 0.7596 |
  | 0.0722        | 5.0   | 39790 | 1.8155          | 0.7615   | 0.7599 |
  | 0.041         | 6.0   | 47748 | 2.1622          | 0.7695   | 0.7678 |
  | 0.0258        | 7.0   | 55706 | 2.3871          | 0.75     | 0.7462 |
  | 0.0149        | 8.0   | 63664 | 2.6135          | 0.7571   | 0.7524 |
  | 0.0076        | 9.0   | 71622 | 2.7974          | 0.7648   | 0.7617 |
  | 0.0051        | 10.0  | 79580 | 2.6982          | 0.7759   | 0.7743 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.10.2
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  