readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: 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. -->
  
  # distilbert-base-uncased-sentiment-finetuned-memes
  
  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: 1.1824
  - Accuracy: 0.8270
  - Precision: 0.8270
  - Recall: 0.8270
  - F1: 0.8270
  
  ## 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: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.5224        | 1.0   | 4293  | 0.5321          | 0.7720   | 0.8084    | 0.7720 | 0.7721 |
  | 0.4386        | 2.0   | 8586  | 0.4930          | 0.7961   | 0.7980    | 0.7961 | 0.7967 |
  | 0.3722        | 3.0   | 12879 | 0.7652          | 0.7925   | 0.7955    | 0.7925 | 0.7932 |
  | 0.3248        | 4.0   | 17172 | 0.9827          | 0.8045   | 0.8047    | 0.8045 | 0.8023 |
  | 0.308         | 5.0   | 21465 | 0.9518          | 0.8244   | 0.8260    | 0.8244 | 0.8249 |
  | 0.2906        | 6.0   | 25758 | 1.0971          | 0.8155   | 0.8166    | 0.8155 | 0.8159 |
  | 0.2036        | 7.0   | 30051 | 1.1457          | 0.8260   | 0.8271    | 0.8260 | 0.8264 |
  | 0.1747        | 8.0   | 34344 | 1.1824          | 0.8270   | 0.8270    | 0.8270 | 0.8270 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  