readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: smalldata-microsoft-deberta-base-eng-only-sentiment-single-finetuned-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. -->
  
  # smalldata-microsoft-deberta-base-eng-only-sentiment-single-finetuned-memes
  
  This model is a fine-tuned version of [jayantapaul888/twitter-data-microsoft-deberta-base-mnli-sentiment-finetuned-memes](https://huggingface.co/jayantapaul888/twitter-data-microsoft-deberta-base-mnli-sentiment-finetuned-memes) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9308
  - Accuracy: 0.8429
  - Precision: 0.8588
  - Recall: 0.8579
  - F1: 0.8583
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | No log        | 1.0   | 378  | 0.3307          | 0.8407   | 0.8682    | 0.8549 | 0.8541 |
  | 0.353         | 2.0   | 756  | 0.3677          | 0.8518   | 0.8669    | 0.8656 | 0.8662 |
  | 0.1726        | 3.0   | 1134 | 0.5219          | 0.8392   | 0.8570    | 0.8549 | 0.8548 |
  | 0.0681        | 4.0   | 1512 | 0.7194          | 0.8414   | 0.8578    | 0.8566 | 0.8572 |
  | 0.0681        | 5.0   | 1890 | 0.8617          | 0.8407   | 0.8573    | 0.8560 | 0.8565 |
  | 0.0233        | 6.0   | 2268 | 0.9308          | 0.8429   | 0.8588    | 0.8579 | 0.8583 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  