metadata
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-pii-masking-augmented-test2
results: []
deberta-pii-masking-augmented-test2
This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0248
- Precision: 0.9565
- Recall: 0.9663
- F1: 0.9613
- Accuracy: 0.9919
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.5574 | 0.16 | 1000 | 0.0750 | 0.8633 | 0.9081 | 0.8851 | 0.9774 |
| 0.0572 | 0.32 | 2000 | 0.0455 | 0.9151 | 0.9290 | 0.9220 | 0.9857 |
| 0.0401 | 0.48 | 3000 | 0.0395 | 0.9294 | 0.9452 | 0.9372 | 0.9873 |
| 0.0319 | 0.64 | 4000 | 0.0301 | 0.9443 | 0.9548 | 0.9496 | 0.9902 |
| 0.0277 | 0.8 | 5000 | 0.0264 | 0.9503 | 0.9618 | 0.9560 | 0.9912 |
| 0.0231 | 0.96 | 6000 | 0.0249 | 0.9538 | 0.9652 | 0.9595 | 0.9920 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1