readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: smalldata-microsoft-deberta-base-mnli-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-mnli-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: 0.7400
  - Accuracy: 0.8816
  - Precision: 0.8946
  - Recall: 0.8937
  - F1: 0.8937
  
  ## 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  | 0.2962          | 0.8764   | 0.8917    | 0.8881 | 0.8884 |
  | 0.3387        | 2.0   | 756  | 0.2803          | 0.8831   | 0.8950    | 0.8942 | 0.8946 |
  | 0.1693        | 3.0   | 1134 | 0.4289          | 0.8764   | 0.8912    | 0.8892 | 0.8886 |
  | 0.0772        | 4.0   | 1512 | 0.5436          | 0.8690   | 0.8822    | 0.8823 | 0.8822 |
  | 0.0772        | 5.0   | 1890 | 0.6566          | 0.8831   | 0.8960    | 0.8947 | 0.8949 |
  | 0.024         | 6.0   | 2268 | 0.7400          | 0.8816   | 0.8946    | 0.8937 | 0.8937 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  