readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: twitter-data-microsoft-xtremedistil-l6-h256-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-microsoft-xtremedistil-l6-h256-uncased-sentiment-finetuned-memes
  
  This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3635
  - Accuracy: 0.8756
  - Precision: 0.8761
  - Recall: 0.8756
  - F1: 0.8755
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.6142        | 1.0   | 1762  | 0.5396          | 0.8022   | 0.8010    | 0.8022 | 0.8014 |
  | 0.4911        | 2.0   | 3524  | 0.4588          | 0.8322   | 0.8332    | 0.8322 | 0.8325 |
  | 0.4511        | 3.0   | 5286  | 0.4072          | 0.8562   | 0.8564    | 0.8562 | 0.8559 |
  | 0.412         | 4.0   | 7048  | 0.3825          | 0.8673   | 0.8680    | 0.8673 | 0.8672 |
  | 0.3886        | 5.0   | 8810  | 0.3677          | 0.8745   | 0.8753    | 0.8745 | 0.8745 |
  | 0.3914        | 6.0   | 10572 | 0.3635          | 0.8756   | 0.8761    | 0.8756 | 0.8755 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  