readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bertweet-base-finetuned-sentiment-analysis
    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. -->
  
  # bertweet-base-finetuned-sentiment-analysis
  
  This model is a fine-tuned version of [cardiffnlp/bertweet-base-sentiment](https://huggingface.co/cardiffnlp/bertweet-base-sentiment) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8458
  - Accuracy: 0.6426
  - F1: 0.6397
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.8904        | 1.0   | 630  | 0.8509          | 0.6381   | 0.6340 |
  | 0.7655        | 2.0   | 1260 | 0.8345          | 0.6579   | 0.6559 |
  | 0.66          | 3.0   | 1890 | 0.9199          | 0.6548   | 0.6514 |
  | 0.447         | 4.0   | 2520 | 1.0324          | 0.6429   | 0.6417 |
  | 0.3585        | 5.0   | 3150 | 1.1234          | 0.6452   | 0.6424 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.12.0
  