readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: distilbert-base-uncased-sentiment-finetuned-memes-20epoch
    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. -->
  
  # distilbert-base-uncased-sentiment-finetuned-memes-20epoch
  
  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: 2.2252
  - Accuracy: 0.8160
  - Precision: 0.8165
  - Recall: 0.8160
  - F1: 0.8162
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.5319        | 1.0   | 4293  | 0.5560          | 0.7699   | 0.7777    | 0.7699 | 0.7704 |
  | 0.4627        | 2.0   | 8586  | 0.6588          | 0.7856   | 0.7868    | 0.7856 | 0.7860 |
  | 0.3735        | 3.0   | 12879 | 0.8583          | 0.7835   | 0.7854    | 0.7835 | 0.7813 |
  | 0.3549        | 4.0   | 17172 | 1.0078          | 0.7872   | 0.7869    | 0.7872 | 0.7866 |
  | 0.2995        | 5.0   | 21465 | 1.0007          | 0.8024   | 0.8030    | 0.8024 | 0.8012 |
  | 0.2579        | 6.0   | 25758 | 1.1501          | 0.8150   | 0.8152    | 0.8150 | 0.8151 |
  | 0.2078        | 7.0   | 30051 | 1.2604          | 0.8097   | 0.8137    | 0.8097 | 0.8102 |
  | 0.1635        | 8.0   | 34344 | 1.3755          | 0.8092   | 0.8092    | 0.8092 | 0.8085 |
  | 0.1453        | 9.0   | 38637 | 1.4639          | 0.8097   | 0.8137    | 0.8097 | 0.8102 |
  | 0.1431        | 10.0  | 42930 | 1.5612          | 0.8050   | 0.8048    | 0.8050 | 0.8044 |
  | 0.085         | 11.0  | 47223 | 1.8216          | 0.8097   | 0.8121    | 0.8097 | 0.8101 |
  | 0.0693        | 12.0  | 51516 | 1.7761          | 0.8087   | 0.8100    | 0.8087 | 0.8090 |
  | 0.041         | 13.0  | 55809 | 1.8538          | 0.8082   | 0.8083    | 0.8082 | 0.8082 |
  | 0.0391        | 14.0  | 60102 | 2.0022          | 0.8160   | 0.8158    | 0.8160 | 0.8158 |
  | 0.0299        | 15.0  | 64395 | 2.0101          | 0.8124   | 0.8121    | 0.8124 | 0.8121 |
  | 0.0226        | 16.0  | 68688 | 2.0396          | 0.8150   | 0.8152    | 0.8150 | 0.8151 |
  | 0.0229        | 17.0  | 72981 | 2.1071          | 0.8171   | 0.8170    | 0.8171 | 0.8171 |
  | 0.0133        | 18.0  | 77274 | 2.1047          | 0.8181   | 0.8182    | 0.8181 | 0.8182 |
  | 0.0268        | 19.0  | 81567 | 2.2037          | 0.8208   | 0.8208    | 0.8208 | 0.8208 |
  | 0.0068        | 20.0  | 85860 | 2.2252          | 0.8160   | 0.8165    | 0.8160 | 0.8162 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  