readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - go_emotions
  metrics:
  - f1
  - accuracy
  model-index:
  - name: bert-base-goemotions
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: go_emotions
        type: go_emotions
        config: simplified
        split: validation
        args: simplified
      metrics:
      - name: F1
        type: f1
        value: 0.5726694586629439
      - name: Accuracy
        type: accuracy
        value: 0.4375230372281607
  ---
  
  <!-- 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. -->
  
  # bert-base-goemotions
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the go_emotions dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1539
  - F1: 0.5727
  - Roc Auc: 0.7796
  - Accuracy: 0.4375
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - 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 | F1     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
  | 0.0833        | 1.0   | 2714  | 0.0876          | 0.5453 | 0.7189  | 0.4243   |
  | 0.0719        | 2.0   | 5428  | 0.0867          | 0.5586 | 0.7322  | 0.4399   |
  | 0.0575        | 3.0   | 8142  | 0.0943          | 0.5736 | 0.7523  | 0.4665   |
  | 0.0411        | 4.0   | 10856 | 0.1064          | 0.5655 | 0.7580  | 0.4574   |
  | 0.0301        | 5.0   | 13570 | 0.1167          | 0.5622 | 0.7591  | 0.4517   |
  | 0.0217        | 6.0   | 16284 | 0.1279          | 0.5579 | 0.7648  | 0.4375   |
  | 0.015         | 7.0   | 18998 | 0.1367          | 0.5663 | 0.7759  | 0.4333   |
  | 0.0102        | 8.0   | 21712 | 0.1445          | 0.5695 | 0.7793  | 0.4322   |
  | 0.0077        | 9.0   | 24426 | 0.1491          | 0.5725 | 0.7795  | 0.4366   |
  | 0.0057        | 10.0  | 27140 | 0.1539          | 0.5727 | 0.7796  | 0.4375   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  