readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncased_finetuned_SPEECH_TEXT_CH_2_DISPLAY
    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_SPEECH_TEXT_CH_2_DISPLAY
  
  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: 1.0863
  - Accuracy: 0.7368
  - F1: 0.7114
  
  ## 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: 40
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.0362        | 1.0   | 19   | 0.9281          | 0.5789   | 0.4964 |
  | 0.9725        | 2.0   | 38   | 0.8906          | 0.6316   | 0.5707 |
  | 0.8712        | 3.0   | 57   | 0.8080          | 0.6316   | 0.5889 |
  | 0.6402        | 4.0   | 76   | 0.6386          | 0.7895   | 0.7474 |
  | 0.4453        | 5.0   | 95   | 0.5401          | 0.7895   | 0.7485 |
  | 0.2658        | 6.0   | 114  | 0.4999          | 0.8421   | 0.7990 |
  | 0.1695        | 7.0   | 133  | 0.6248          | 0.7895   | 0.7427 |
  | 0.0822        | 8.0   | 152  | 0.7391          | 0.7368   | 0.7114 |
  | 0.0303        | 9.0   | 171  | 0.6665          | 0.7895   | 0.7485 |
  | 0.016         | 10.0  | 190  | 0.8217          | 0.7368   | 0.7114 |
  | 0.0103        | 11.0  | 209  | 0.8090          | 0.7368   | 0.7114 |
  | 0.0083        | 12.0  | 228  | 0.8646          | 0.7368   | 0.7114 |
  | 0.0068        | 13.0  | 247  | 0.9091          | 0.7368   | 0.7114 |
  | 0.0059        | 14.0  | 266  | 0.8731          | 0.7368   | 0.7114 |
  | 0.0049        | 15.0  | 285  | 0.9512          | 0.7368   | 0.7114 |
  | 0.0048        | 16.0  | 304  | 0.9376          | 0.7368   | 0.7114 |
  | 0.004         | 17.0  | 323  | 0.9507          | 0.7368   | 0.7114 |
  | 0.0037        | 18.0  | 342  | 0.9868          | 0.7368   | 0.7114 |
  | 0.0033        | 19.0  | 361  | 0.9862          | 0.7368   | 0.7114 |
  | 0.0029        | 20.0  | 380  | 0.9733          | 0.7368   | 0.7114 |
  | 0.0029        | 21.0  | 399  | 0.9747          | 0.7368   | 0.7114 |
  | 0.0027        | 22.0  | 418  | 0.9998          | 0.7368   | 0.7114 |
  | 0.0024        | 23.0  | 437  | 0.9984          | 0.7368   | 0.7114 |
  | 0.0024        | 24.0  | 456  | 1.0270          | 0.7368   | 0.7114 |
  | 0.0024        | 25.0  | 475  | 1.0083          | 0.7368   | 0.7114 |
  | 0.0022        | 26.0  | 494  | 1.0167          | 0.7368   | 0.7114 |
  | 0.0021        | 27.0  | 513  | 1.0273          | 0.7368   | 0.7114 |
  | 0.002         | 28.0  | 532  | 1.0340          | 0.7368   | 0.7114 |
  | 0.0021        | 29.0  | 551  | 1.0282          | 0.7368   | 0.7114 |
  | 0.002         | 30.0  | 570  | 1.0372          | 0.7368   | 0.7114 |
  | 0.0019        | 31.0  | 589  | 1.0593          | 0.7368   | 0.7114 |
  | 0.0017        | 32.0  | 608  | 1.0841          | 0.7368   | 0.7114 |
  | 0.0018        | 33.0  | 627  | 1.0920          | 0.7368   | 0.7114 |
  | 0.0019        | 34.0  | 646  | 1.0943          | 0.7368   | 0.7114 |
  | 0.0018        | 35.0  | 665  | 1.0883          | 0.7368   | 0.7114 |
  | 0.0017        | 36.0  | 684  | 1.0864          | 0.7368   | 0.7114 |
  | 0.0016        | 37.0  | 703  | 1.0890          | 0.7368   | 0.7114 |
  | 0.0017        | 38.0  | 722  | 1.0894          | 0.7368   | 0.7114 |
  | 0.0015        | 39.0  | 741  | 1.0867          | 0.7368   | 0.7114 |
  | 0.0016        | 40.0  | 760  | 1.0863          | 0.7368   | 0.7114 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.10.2
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  