---
library_name: transformers
license: mit
base_model: BAAI/bge-small-en-v1.5
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bge-small-en-v1.5-ultrafineweb-vs-pile-classifier
  results: []
datasets:
- openbmb/Ultra-FineWeb
- EleutherAI/the_pile_deduplicated
language:
- en
pipeline_tag: text-classification
---

# bge-small-en-v1.5-ultrafineweb-vs-pile-classifier

> [!IMPORTANT]  
> **Note:** This model is provided for reference and reproducibility, not for standalone use.

This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) 
to classify text as high quality or low quality for AI training.

- Trained on 100k samples from [openbmb/Ultra-FineWeb](https://huggingface.co/datasets/openbmb/Ultra-FineWeb) (high quality) and 100k from [EleutherAI/the_pile_deduplicated](https://huggingface.co/datasets/EleutherAI/the_pile_deduplicated) (low quality)  
- 80% training / 20% validation split  

On the validation set:
- Loss: 0.2926  
- Accuracy: 0.9061  
- Combined Score: 2.1448  
- Tokens processed: 102,184,960

## Example

```python
from transformers import pipeline

classifier = pipeline("text-classification", model="agentlans/bge-small-en-v1.5-ultrafineweb-vs-pile-classifier")
classifier("Your text here.")
```

## Limitations  
- Tends to be overly strict, labelling most texts outside training data as low quality  
- English only  
- May be biased against some text types such as source code and personal blogs

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Combined Score | Input Tokens Seen |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------------:|:-----------------:|
| 0.2893        | 1.0   | 19958 | 0.2926          | 0.9061   | 2.1448         | 20436992          |
| 0.2397        | 2.0   | 39916 | 0.3127          | 0.9076   | 2.1194         | 40873984          |
| 0.2           | 3.0   | 59874 | 0.3279          | 0.9109   | 2.0605         | 61310976          |
| 0.1576        | 4.0   | 79832 | 0.3887          | 0.9080   | 2.1119         | 81747968          |
| 0.1127        | 5.0   | 99790 | 0.4688          | 0.9069   | 2.1308         | 102184960         |

### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0