readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-roberta-base-sentiment-sentiment-memes
    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-sentiment-sentiment-memes
  
  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9582
  - Accuracy: 0.8187
  - Precision: 0.8199
  - Recall: 0.8187
  - F1: 0.8191
  
  ## 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.4673        | 1.0   | 2147  | 0.4373          | 0.7647   | 0.8180    | 0.7647 | 0.7657 |
  | 0.3987        | 2.0   | 4294  | 0.5528          | 0.7783   | 0.8096    | 0.7783 | 0.7804 |
  | 0.3194        | 3.0   | 6441  | 0.6432          | 0.7752   | 0.7767    | 0.7752 | 0.7680 |
  | 0.2855        | 4.0   | 8588  | 0.6820          | 0.7814   | 0.8034    | 0.7814 | 0.7837 |
  | 0.2575        | 5.0   | 10735 | 0.7427          | 0.7720   | 0.8070    | 0.7720 | 0.7741 |
  | 0.2154        | 6.0   | 12882 | 0.8225          | 0.7987   | 0.8062    | 0.7987 | 0.8004 |
  | 0.2195        | 7.0   | 15029 | 0.8361          | 0.8071   | 0.8086    | 0.8071 | 0.8077 |
  | 0.2322        | 8.0   | 17176 | 0.8842          | 0.8056   | 0.8106    | 0.8056 | 0.8069 |
  | 0.2102        | 9.0   | 19323 | 0.9188          | 0.8129   | 0.8144    | 0.8129 | 0.8135 |
  | 0.1893        | 10.0  | 21470 | 0.9582          | 0.8187   | 0.8199    | 0.8187 | 0.8191 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 1.15.2.dev0
  - Tokenizers 0.10.1
  