readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - financial_phrasebank
  metrics:
  - recall
  - accuracy
  - precision
  model-index:
  - name: TOMFINSEN
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: financial_phrasebank
        type: financial_phrasebank
        args: sentences_50agree
      metrics:
      - name: Recall
        type: recall
        value: 0.8985861629736692
      - name: Accuracy
        type: accuracy
        value: 0.8742268041237113
      - name: Precision
        type: precision
        value: 0.8509995913451198
  ---
  
  <!-- 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. -->
  
  # TOMFINSEN
  
  This model is a fine-tuned version of [deepmind/language-perceiver](https://huggingface.co/deepmind/language-perceiver) on the financial_phrasebank dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3642
  - Recall: 0.8986
  - Accuracy: 0.8742
  - Precision: 0.8510
  
  ## 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
  - distributed_type: tpu
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Recall | Accuracy | Precision |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|
  | 0.5403        | 1.0   | 273  | 0.4207          | 0.8358 | 0.8619   | 0.8534    |
  | 0.3939        | 2.0   | 546  | 0.3750          | 0.8943 | 0.8577   | 0.8225    |
  | 0.1993        | 3.0   | 819  | 0.3113          | 0.8882 | 0.8660   | 0.8367    |
  | 0.301         | 4.0   | 1092 | 0.3642          | 0.8986 | 0.8742   | 0.8510    |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.9.0+cu102
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  