---
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