|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
base_model: microsoft/deberta-v3-small |
|
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 |
|
|
