---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/phi-2
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: phi-finetuned-spam
  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. -->

# phi-finetuned-spam

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0822
- Accuracy: 0.989
- F1: 0.9890
- Precision: 0.9880
- Recall: 0.99

## 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: 3.628060796399553e-05
- train_batch_size: 8
- eval_batch_size: 2
- seed: 31
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1312        | 1.0   | 1125 | 0.1122          | 0.974    | 0.9735 | 0.9917    | 0.956  |
| 0.0224        | 2.0   | 2250 | 0.0822          | 0.989    | 0.9890 | 0.9880    | 0.99   |
| 0.0654        | 3.0   | 3375 | 0.0806          | 0.988    | 0.988  | 0.988     | 0.988  |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1