---
license: mit
base_model: BAAI/bge-small-en-v1.5
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bge-small-en-v1.5-sms-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. -->

# bge-small-en-v1.5-sms-spam

This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0328
- Accuracy: 0.9928
- Precision: 0.9928
- Recall: 0.9928
- F1: 0.9928

## 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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 244  | 0.0481          | 0.9904   | 0.9904    | 0.9904 | 0.9904 |
| No log        | 2.0   | 488  | 0.0435          | 0.9916   | 0.9918    | 0.9916 | 0.9917 |
| 0.0902        | 3.0   | 732  | 0.0379          | 0.9904   | 0.9904    | 0.9904 | 0.9903 |
| 0.0902        | 4.0   | 976  | 0.0350          | 0.9916   | 0.9916    | 0.9916 | 0.9916 |
| 0.0173        | 5.0   | 1220 | 0.0328          | 0.9928   | 0.9928    | 0.9928 | 0.9928 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2