readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - financial_phrasebank
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncased_allagree3
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: financial_phrasebank
        type: financial_phrasebank
        args: sentences_allagree
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9778761061946902
      - name: F1
        type: f1
        value: 0.9780006392634297
  ---
  
  <!-- 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. -->
  
  # distilbert-base-uncased_allagree3
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the financial_phrasebank dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0937
  - Accuracy: 0.9779
  - F1: 0.9780
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.6418        | 1.0   | 57   | 0.3340          | 0.8805   | 0.8768 |
  | 0.1821        | 2.0   | 114  | 0.1088          | 0.9690   | 0.9691 |
  | 0.0795        | 3.0   | 171  | 0.0822          | 0.9823   | 0.9823 |
  | 0.0385        | 4.0   | 228  | 0.0939          | 0.9646   | 0.9646 |
  | 0.0218        | 5.0   | 285  | 0.1151          | 0.9735   | 0.9737 |
  | 0.0149        | 6.0   | 342  | 0.1126          | 0.9690   | 0.9694 |
  | 0.006         | 7.0   | 399  | 0.0989          | 0.9779   | 0.9780 |
  | 0.0093        | 8.0   | 456  | 0.1009          | 0.9779   | 0.9780 |
  | 0.0063        | 9.0   | 513  | 0.0899          | 0.9779   | 0.9780 |
  | 0.0039        | 10.0  | 570  | 0.0937          | 0.9779   | 0.9780 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cpu
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  