readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncased_Up_Sampling_Sub_Category_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_Up_Sampling_Sub_Category_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: 4.9368
  - Accuracy: 0.6114
  - F1: 0.6028
  
  ## 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     |
  |:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|
  | 0.9716        | 1.0   | 12171  | 2.5228          | 0.5722   | 0.5740 |
  | 0.2857        | 2.0   | 24342  | 3.0558          | 0.5947   | 0.5923 |
  | 0.1438        | 3.0   | 36513  | 3.3499          | 0.6038   | 0.6007 |
  | 0.0842        | 4.0   | 48684  | 3.8879          | 0.5905   | 0.5875 |
  | 0.0504        | 5.0   | 60855  | 4.1478          | 0.5905   | 0.5906 |
  | 0.031         | 6.0   | 73026  | 4.5368          | 0.5924   | 0.5865 |
  | 0.0192        | 7.0   | 85197  | 4.6596          | 0.6042   | 0.5980 |
  | 0.01          | 8.0   | 97368  | 4.8874          | 0.6087   | 0.6005 |
  | 0.0051        | 9.0   | 109539 | 5.0120          | 0.6118   | 0.6015 |
  | 0.0022        | 10.0  | 121710 | 4.9368          | 0.6114   | 0.6028 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.10.2
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  