readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-data-distilbert-base-uncased-sentiment-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. -->
  
  # twitter-data-distilbert-base-uncased-sentiment-finetuned-memes
  
  This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2474
  - Accuracy: 0.9282
  - Precision: 0.9290
  - Recall: 0.9282
  - F1: 0.9282
  
  ## 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: 1e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.3623        | 1.0   | 1762  | 0.3171          | 0.8986   | 0.8995    | 0.8986 | 0.8981 |
  | 0.271         | 2.0   | 3524  | 0.2665          | 0.9176   | 0.9182    | 0.9176 | 0.9173 |
  | 0.2386        | 3.0   | 5286  | 0.2499          | 0.9237   | 0.9254    | 0.9237 | 0.9239 |
  | 0.2136        | 4.0   | 7048  | 0.2494          | 0.9259   | 0.9263    | 0.9259 | 0.9257 |
  | 0.1974        | 5.0   | 8810  | 0.2454          | 0.9278   | 0.9288    | 0.9278 | 0.9278 |
  | 0.182         | 6.0   | 10572 | 0.2474          | 0.9282   | 0.9290    | 0.9282 | 0.9282 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  