---
license: gemma
library_name: peft
tags:
- generated_from_trainer
base_model: google/gemma-2b
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: gemma-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. -->

# gemma-finetuned-spam

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co./google/gemma-2b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0545
- Accuracy: 0.994
- F1: 0.994
- Precision: 0.994
- Recall: 0.994

## 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: 3.589634237431302e-05
- train_batch_size: 8
- eval_batch_size: 2
- seed: 3
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0491        | 1.0   | 1125 | 0.0730          | 0.989    | 0.9890 | 0.9861    | 0.992  |
| 0.0253        | 2.0   | 2250 | 0.0516          | 0.99     | 0.9900 | 0.9920    | 0.988  |
| 0.006         | 3.0   | 3375 | 0.0546          | 0.993    | 0.9930 | 0.9920    | 0.994  |
| 0.0           | 4.0   | 4500 | 0.0545          | 0.994    | 0.994  | 0.994     | 0.994  |
| 0.0001        | 5.0   | 5625 | 0.0554          | 0.994    | 0.994  | 0.994     | 0.994  |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1