readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: roberta-twitter-spam-classifier
    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. -->
  
  # roberta-twitter-spam-classifier
  
  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3856
  - Micro-avg-precision: 0.8723
  - Micro-avg-recall: 0.8490
  - Micro-avg-f1-score: 0.8594
  
  ## 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: 8
  - eval_batch_size: 32
  - 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 | Micro-avg-precision | Micro-avg-recall | Micro-avg-f1-score |
  |:-------------:|:-----:|:-----:|:---------------:|:-------------------:|:----------------:|:------------------:|
  | 0.4923        | 1.0   | 2762  | 0.5676          | 0.8231              | 0.6494           | 0.6676             |
  | 0.535         | 2.0   | 5524  | 0.4460          | 0.8065              | 0.8215           | 0.8132             |
  | 0.5492        | 3.0   | 8286  | 0.6005          | 0.6635              | 0.5843           | 0.3906             |
  | 0.5947        | 4.0   | 11048 | 0.5710          | 0.7875              | 0.7799           | 0.7835             |
  | 0.4976        | 5.0   | 13810 | 0.5194          | 0.8375              | 0.7544           | 0.7800             |
  | 0.5263        | 6.0   | 16572 | 0.5491          | 0.8739              | 0.7159           | 0.7475             |
  | 0.4701        | 7.0   | 19334 | 0.4609          | 0.8681              | 0.7786           | 0.8069             |
  | 0.4566        | 8.0   | 22096 | 0.4100          | 0.8637              | 0.8281           | 0.8430             |
  | 0.4339        | 9.0   | 24858 | 0.4395          | 0.8642              | 0.8454           | 0.8540             |
  | 0.3906        | 10.0  | 27620 | 0.3856          | 0.8723              | 0.8490           | 0.8594             |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.2
  - Tokenizers 0.11.0
  