readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - finer-139
  - nlpaueb/finer-139
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bertiny-finetuned-finer
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: finer-139
        type: finer-139
        args: finer-139
      metrics:
      - name: Precision
        type: precision
        value: 0.5339285714285714
      - name: Recall
        type: recall
        value: 0.036011080332409975
      - name: F1
        type: f1
        value: 0.06747151077513258
      - name: Accuracy
        type: accuracy
        value: 0.9847166143263048
  ---
  
  <!-- 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. -->
  
  # bertiny-finetuned-finer
  
  This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the finer-139 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0882
  - Precision: 0.5339
  - Recall: 0.0360
  - F1: 0.0675
  - Accuracy: 0.9847
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.0871        | 1.0   | 11255 | 0.0952          | 0.0       | 0.0    | 0.0    | 0.9843   |
  | 0.0864        | 2.0   | 22510 | 0.0895          | 0.7640    | 0.0082 | 0.0162 | 0.9844   |
  | 0.0929        | 3.0   | 33765 | 0.0882          | 0.5339    | 0.0360 | 0.0675 | 0.9847   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  