readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: twhin-bert-large-finetuned-fintwitter-classification
    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. -->
  
  # twhin-bert-large-finetuned-fintwitter-classification
  
  This model is a fine-tuned version of [Twitter/twhin-bert-large](https://huggingface.co/Twitter/twhin-bert-large) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6936
  - Accuracy: 0.8903
  - F1: 0.8903
  - Precision: 0.8903
  - Recall: 0.8903
  
  ## 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: 128
  - eval_batch_size: 128
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | No log        | 1.0   | 75   | 0.5087          | 0.7835   | 0.7594 | 0.7846    | 0.7835 |
  | No log        | 2.0   | 150  | 0.3652          | 0.8685   | 0.8696 | 0.8735    | 0.8685 |
  | No log        | 3.0   | 225  | 0.3452          | 0.8723   | 0.8739 | 0.8772    | 0.8723 |
  | No log        | 4.0   | 300  | 0.3332          | 0.8823   | 0.8830 | 0.8840    | 0.8823 |
  | No log        | 5.0   | 375  | 0.3618          | 0.8907   | 0.8909 | 0.8912    | 0.8907 |
  | No log        | 6.0   | 450  | 0.3995          | 0.8802   | 0.8807 | 0.8814    | 0.8802 |
  | 0.2712        | 7.0   | 525  | 0.4459          | 0.8886   | 0.8888 | 0.8889    | 0.8886 |
  | 0.2712        | 8.0   | 600  | 0.5018          | 0.8903   | 0.8897 | 0.8894    | 0.8903 |
  | 0.2712        | 9.0   | 675  | 0.5457          | 0.8836   | 0.8844 | 0.8860    | 0.8836 |
  | 0.2712        | 10.0  | 750  | 0.5562          | 0.8723   | 0.8725 | 0.8750    | 0.8723 |
  | 0.2712        | 11.0  | 825  | 0.6080          | 0.8827   | 0.8827 | 0.8828    | 0.8827 |
  | 0.2712        | 12.0  | 900  | 0.5886          | 0.8853   | 0.8852 | 0.8851    | 0.8853 |
  | 0.2712        | 13.0  | 975  | 0.6021          | 0.8874   | 0.8878 | 0.8890    | 0.8874 |
  | 0.0383        | 14.0  | 1050 | 0.5960          | 0.8853   | 0.8849 | 0.8846    | 0.8853 |
  | 0.0383        | 15.0  | 1125 | 0.6393          | 0.8815   | 0.8819 | 0.8827    | 0.8815 |
  | 0.0383        | 16.0  | 1200 | 0.6803          | 0.8844   | 0.8852 | 0.8865    | 0.8844 |
  | 0.0383        | 17.0  | 1275 | 0.6839          | 0.8915   | 0.8915 | 0.8914    | 0.8915 |
  | 0.0383        | 18.0  | 1350 | 0.6968          | 0.8907   | 0.8901 | 0.8899    | 0.8907 |
  | 0.0383        | 19.0  | 1425 | 0.6971          | 0.8865   | 0.8870 | 0.8878    | 0.8865 |
  | 0.0122        | 20.0  | 1500 | 0.6936          | 0.8903   | 0.8903 | 0.8903    | 0.8903 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  