readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - go_emotions
  metrics:
  - f1
  - accuracy
  model-index:
  - name: pretrained_model
    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: 0.572835583796664
      - name: Accuracy
        type: accuracy
        value: 0.45466273497972726
  ---
  
  <!-- 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. -->
  
  # pretrained_model
  
  This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the go_emotions dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1240
  - F1: 0.5728
  - Roc Auc: 0.7737
  - Accuracy: 0.4547
  
  ## 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: 64
  - eval_batch_size: 64
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
  | 0.1205        | 1.0   | 679  | 0.0865          | 0.5632 | 0.7347  | 0.4458   |
  | 0.0859        | 2.0   | 1358 | 0.0829          | 0.5717 | 0.7378  | 0.4521   |
  | 0.0727        | 3.0   | 2037 | 0.0827          | 0.5897 | 0.7523  | 0.4753   |
  | 0.0629        | 4.0   | 2716 | 0.0857          | 0.5808 | 0.7535  | 0.4652   |
  | 0.0568        | 5.0   | 3395 | 0.0904          | 0.5868 | 0.7616  | 0.4821   |
  | 0.0423        | 6.0   | 4074 | 0.0989          | 0.5806 | 0.7682  | 0.4724   |
  | 0.0344        | 7.0   | 4753 | 0.1079          | 0.5736 | 0.7657  | 0.4650   |
  | 0.0296        | 8.0   | 5432 | 0.1158          | 0.5637 | 0.7649  | 0.4504   |
  | 0.0206        | 9.0   | 6111 | 0.1200          | 0.5674 | 0.7689  | 0.4486   |
  | 0.0177        | 10.0  | 6790 | 0.1240          | 0.5728 | 0.7737  | 0.4547   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  