metadata

license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: phi-3-mini-NER-PII-Vast3
    results: []

phi-3-mini-NER-PII-Vast3

This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1122
Precision: 0.6826
Recall: 0.8382
F1: 0.7524
Accuracy: 0.9697

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 3

Training results

Training Loss	Epoch	Step	Accuracy	F1	Validation Loss	Precision	Recall
0.1017	1.0	11105	0.9693	0.7506	0.1123	0.6807	0.8364
0.0782	2.0	22210	0.1119	0.6819	0.8382	0.7520	0.9697
0.0944	3.0	33315	0.1122	0.6826	0.8382	0.7524	0.9697

Framework versions

Transformers 4.41.1
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.19.1