readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: bert-finetuned-sentiment
    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. -->
  
  # bert-finetuned-sentiment
  
  This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4884
  - Accuracy: 0.7698
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6778        | 1.0   | 722  | 0.7149          | 0.7482   |
  | 0.3768        | 2.0   | 1444 | 0.9821          | 0.7410   |
  | 0.1612        | 3.0   | 2166 | 1.4027          | 0.7662   |
  | 0.094         | 4.0   | 2888 | 1.4884          | 0.7698   |
  | 0.0448        | 5.0   | 3610 | 1.6463          | 0.7590   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  