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-v1
    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-v1
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2426
  - Accuracy: 0.6492
  - Precision: 0.6498
  - Recall: 0.6492
  - F1: 0.6492
  
  ## 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: 16
  - eval_batch_size: 16
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.8263        | 1.0   | 663  | 0.7315          | 0.6536   | 0.6699    | 0.6536 | 0.6502 |
  | 0.6658        | 2.0   | 1326 | 0.7801          | 0.6565   | 0.6613    | 0.6565 | 0.6560 |
  | 0.5735        | 3.0   | 1989 | 0.8170          | 0.6514   | 0.6579    | 0.6514 | 0.6504 |
  | 0.344         | 4.0   | 2652 | 1.0184          | 0.6512   | 0.6525    | 0.6512 | 0.6512 |
  | 0.2671        | 5.0   | 3315 | 1.1672          | 0.6503   | 0.6519    | 0.6503 | 0.6504 |
  | 0.2236        | 6.0   | 3978 | 1.2426          | 0.6492   | 0.6498    | 0.6492 | 0.6492 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  