readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncased-finetuned-emotion
    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-emotion
  
  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: 1.0202
  - Accuracy: 0.8235
  - F1: 0.8223
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.7099        | 1.0   | 17   | 0.6695          | 0.5294   | 0.3665 |
  | 0.686         | 2.0   | 34   | 0.6288          | 0.5294   | 0.3665 |
  | 0.5945        | 3.0   | 51   | 0.4339          | 0.8824   | 0.8824 |
  | 0.3718        | 4.0   | 68   | 0.3600          | 0.8235   | 0.8235 |
  | 0.1248        | 5.0   | 85   | 0.5730          | 0.8235   | 0.8223 |
  | 0.0984        | 6.0   | 102  | 0.7659          | 0.7647   | 0.7647 |
  | 0.0138        | 7.0   | 119  | 0.8271          | 0.8235   | 0.8223 |
  | 0.0121        | 8.0   | 136  | 0.8223          | 0.8235   | 0.8223 |
  | 0.0062        | 9.0   | 153  | 0.7349          | 0.8235   | 0.8223 |
  | 0.0045        | 10.0  | 170  | 0.8381          | 0.7647   | 0.7597 |
  | 0.0037        | 11.0  | 187  | 0.8636          | 0.7647   | 0.7597 |
  | 0.0031        | 12.0  | 204  | 0.8603          | 0.8235   | 0.8223 |
  | 0.0025        | 13.0  | 221  | 0.8714          | 0.8235   | 0.8223 |
  | 0.0021        | 14.0  | 238  | 0.8864          | 0.8235   | 0.8223 |
  | 0.002         | 15.0  | 255  | 0.9114          | 0.8235   | 0.8223 |
  | 0.0017        | 16.0  | 272  | 0.9295          | 0.8235   | 0.8223 |
  | 0.0014        | 17.0  | 289  | 0.9360          | 0.8235   | 0.8223 |
  | 0.0013        | 18.0  | 306  | 0.9378          | 0.8235   | 0.8223 |
  | 0.0012        | 19.0  | 323  | 0.9429          | 0.8235   | 0.8223 |
  | 0.0012        | 20.0  | 340  | 0.9528          | 0.8235   | 0.8223 |
  | 0.0011        | 21.0  | 357  | 0.9609          | 0.8235   | 0.8223 |
  | 0.001         | 22.0  | 374  | 0.9667          | 0.8235   | 0.8223 |
  | 0.001         | 23.0  | 391  | 0.9738          | 0.8235   | 0.8223 |
  | 0.001         | 24.0  | 408  | 0.9804          | 0.8235   | 0.8223 |
  | 0.0009        | 25.0  | 425  | 0.9827          | 0.8235   | 0.8223 |
  | 0.0009        | 26.0  | 442  | 0.9863          | 0.8235   | 0.8223 |
  | 0.0008        | 27.0  | 459  | 0.9910          | 0.8235   | 0.8223 |
  | 0.0008        | 28.0  | 476  | 0.9949          | 0.8235   | 0.8223 |
  | 0.0007        | 29.0  | 493  | 1.0002          | 0.8235   | 0.8223 |
  | 0.0008        | 30.0  | 510  | 1.0042          | 0.8235   | 0.8223 |
  | 0.0007        | 31.0  | 527  | 1.0058          | 0.8235   | 0.8223 |
  | 0.0007        | 32.0  | 544  | 1.0091          | 0.8235   | 0.8223 |
  | 0.0006        | 33.0  | 561  | 1.0118          | 0.8235   | 0.8223 |
  | 0.0006        | 34.0  | 578  | 1.0148          | 0.8235   | 0.8223 |
  | 0.0007        | 35.0  | 595  | 1.0163          | 0.8235   | 0.8223 |
  | 0.0006        | 36.0  | 612  | 1.0174          | 0.8235   | 0.8223 |
  | 0.0006        | 37.0  | 629  | 1.0185          | 0.8235   | 0.8223 |
  | 0.0006        | 38.0  | 646  | 1.0194          | 0.8235   | 0.8223 |
  | 0.0006        | 39.0  | 663  | 1.0200          | 0.8235   | 0.8223 |
  | 0.0006        | 40.0  | 680  | 1.0202          | 0.8235   | 0.8223 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.10.2
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  