File size: 1,800 Bytes
8a4b340 fff7f0c 8a4b340 fff7f0c 8a4b340 fff7f0c 8a4b340 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
---
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
|