readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - tweet_eval
  model-index:
  - name: roberta-sentiment-analysis-finetune
    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. -->
  
  # roberta-sentiment-analysis-finetune
  
  This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on the tweet_eval dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8863
  
  ## 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
  - lr_scheduler_warmup_steps: 50
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.5451        | 1.0   | 713  | 0.5422          |
  | 0.4785        | 2.0   | 1426 | 0.5585          |
  | 0.4199        | 3.0   | 2139 | 0.5785          |
  | 0.3608        | 4.0   | 2852 | 0.6038          |
  | 0.3117        | 5.0   | 3565 | 0.6713          |
  | 0.2684        | 6.0   | 4278 | 0.7366          |
  | 0.2403        | 7.0   | 4991 | 0.7737          |
  | 0.2137        | 8.0   | 5704 | 0.8276          |
  | 0.1926        | 9.0   | 6417 | 0.8597          |
  | 0.1778        | 10.0  | 7130 | 0.8863          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  