readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncased_finetuned_SPEECH_TEXT_CH_1_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_1_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: 0.7615
  - Accuracy: 0.7895
  - F1: 0.8006
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.0411        | 1.0   | 19   | 0.9506          | 0.4737   | 0.3045 |
  | 0.9515        | 2.0   | 38   | 0.9126          | 0.5789   | 0.4964 |
  | 0.9064        | 3.0   | 57   | 0.8215          | 0.7368   | 0.6977 |
  | 0.7414        | 4.0   | 76   | 0.6747          | 0.7895   | 0.7447 |
  | 0.4968        | 5.0   | 95   | 0.5658          | 0.8947   | 0.8474 |
  | 0.2849        | 6.0   | 114  | 0.5001          | 0.8421   | 0.7953 |
  | 0.1576        | 7.0   | 133  | 0.4605          | 0.8421   | 0.7953 |
  | 0.0705        | 8.0   | 152  | 0.6264          | 0.7895   | 0.7822 |
  | 0.0297        | 9.0   | 171  | 0.5283          | 0.8421   | 0.8561 |
  | 0.0142        | 10.0  | 190  | 0.5972          | 0.7368   | 0.7441 |
  | 0.0107        | 11.0  | 209  | 0.5542          | 0.8421   | 0.8561 |
  | 0.0079        | 12.0  | 228  | 0.5919          | 0.8421   | 0.8561 |
  | 0.0067        | 13.0  | 247  | 0.6106          | 0.7895   | 0.8006 |
  | 0.0055        | 14.0  | 266  | 0.6232          | 0.8421   | 0.8561 |
  | 0.0049        | 15.0  | 285  | 0.6478          | 0.8421   | 0.8561 |
  | 0.0043        | 16.0  | 304  | 0.6465          | 0.8421   | 0.8561 |
  | 0.0038        | 17.0  | 323  | 0.6618          | 0.7895   | 0.8006 |
  | 0.0034        | 18.0  | 342  | 0.6669          | 0.8421   | 0.8561 |
  | 0.0032        | 19.0  | 361  | 0.6737          | 0.8421   | 0.8561 |
  | 0.003         | 20.0  | 380  | 0.6808          | 0.7895   | 0.8006 |
  | 0.0028        | 21.0  | 399  | 0.6890          | 0.7895   | 0.8006 |
  | 0.0026        | 22.0  | 418  | 0.7081          | 0.7895   | 0.8006 |
  | 0.0025        | 23.0  | 437  | 0.7146          | 0.7895   | 0.8006 |
  | 0.0023        | 24.0  | 456  | 0.7182          | 0.7895   | 0.8006 |
  | 0.0022        | 25.0  | 475  | 0.7248          | 0.7895   | 0.8006 |
  | 0.002         | 26.0  | 494  | 0.7419          | 0.7895   | 0.8006 |
  | 0.0019        | 27.0  | 513  | 0.7390          | 0.7895   | 0.8006 |
  | 0.0021        | 28.0  | 532  | 0.7379          | 0.7895   | 0.8006 |
  | 0.0019        | 29.0  | 551  | 0.7392          | 0.7895   | 0.8006 |
  | 0.0019        | 30.0  | 570  | 0.7362          | 0.7895   | 0.8006 |
  | 0.0019        | 31.0  | 589  | 0.7395          | 0.7895   | 0.8006 |
  | 0.0019        | 32.0  | 608  | 0.7436          | 0.7895   | 0.8006 |
  | 0.0017        | 33.0  | 627  | 0.7509          | 0.7895   | 0.8006 |
  | 0.0018        | 34.0  | 646  | 0.7563          | 0.7895   | 0.8006 |
  | 0.0016        | 35.0  | 665  | 0.7597          | 0.7895   | 0.8006 |
  | 0.0017        | 36.0  | 684  | 0.7617          | 0.7895   | 0.8006 |
  | 0.0016        | 37.0  | 703  | 0.7625          | 0.7895   | 0.8006 |
  | 0.0017        | 38.0  | 722  | 0.7615          | 0.7895   | 0.8006 |
  | 0.0017        | 39.0  | 741  | 0.7617          | 0.7895   | 0.8006 |
  | 0.0015        | 40.0  | 760  | 0.7615          | 0.7895   | 0.8006 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.10.2
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  