readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - tweet_eval
  metrics:
  - accuracy
  - f1
  model-index:
  - name: tiny-mlm-tweet-target-tweet
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: tweet_eval
        type: tweet_eval
        config: emotion
        split: train
        args: emotion
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.7165775401069518
      - name: F1
        type: f1
        value: 0.7162540037184906
  ---
  
  <!-- 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. -->
  
  # tiny-mlm-tweet-target-tweet
  
  This model is a fine-tuned version of [muhtasham/tiny-mlm-tweet](https://huggingface.co/muhtasham/tiny-mlm-tweet) on the tweet_eval dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2643
  - Accuracy: 0.7166
  - F1: 0.7163
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: constant
  - num_epochs: 200
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.1435        | 4.9   | 500  | 0.9732          | 0.6604   | 0.6283 |
  | 0.7389        | 9.8   | 1000 | 0.8571          | 0.6898   | 0.6780 |
  | 0.5057        | 14.71 | 1500 | 0.8324          | 0.6979   | 0.6929 |
  | 0.3466        | 19.61 | 2000 | 0.9128          | 0.6925   | 0.6945 |
  | 0.2395        | 24.51 | 2500 | 0.9487          | 0.7166   | 0.7192 |
  | 0.1649        | 29.41 | 3000 | 1.0338          | 0.7166   | 0.7172 |
  | 0.119         | 34.31 | 3500 | 1.1793          | 0.7112   | 0.7144 |
  | 0.0882        | 39.22 | 4000 | 1.2643          | 0.7166   | 0.7163 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  