readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: nlp-redaction-classifier
    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. -->
  
  # Redaction Classifier: NLP Edition
  
  This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on a custom dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0893
  - Pearson: 0.8273
  
  ## Model description
  
  Read more about the process and the code used to train this model on my blog [here](https://mlops.systems).
  
  ## 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: 0.0001
  - train_batch_size: 4
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 6
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Pearson |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.2054        | 1.0   | 729  | 0.1382          | 0.6771  |
  | 0.1386        | 2.0   | 1458 | 0.1099          | 0.7721  |
  | 0.0782        | 3.0   | 2187 | 0.0950          | 0.8083  |
  | 0.054         | 4.0   | 2916 | 0.0945          | 0.8185  |
  | 0.0319        | 5.0   | 3645 | 0.0880          | 0.8251  |
  | 0.0254        | 6.0   | 4374 | 0.0893          | 0.8273  |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0a0+17540c5
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  