readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-roberta-base-dec2021_rbam_fine_tuned
    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. -->
  
  # twitter-roberta-base-dec2021_rbam_fine_tuned
  
  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-dec2021](https://huggingface.co/cardiffnlp/twitter-roberta-base-dec2021) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8295
  - Accuracy: 0.6777
  - Precision: 0.6743
  - Recall: 0.6777
  - F1: 0.6753
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.8455        | 1.0   | 3264 | 0.7663          | 0.6661   | 0.6802    | 0.6661 | 0.6693 |
  | 0.6421        | 2.0   | 6528 | 0.8295          | 0.6777   | 0.6743    | 0.6777 | 0.6753 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  