README.md

---
library_name: transformers
datasets:
- MoritzLaurer/synthetic_zeroshot_mixtral_v0.1
language:
- en
base_model:
- answerdotai/ModernBERT-large
pipeline_tag: zero-shot-classification
license: mit
---


### Model Description

This model is a fine-tuned **ModernBERT-large** for **Natural Language Inference**. It was trained on the [MoritzLaurer/synthetic_zeroshot_mixtral_v0.1](https://huggingface.co/datasets/MoritzLaurer/synthetic_zeroshot_mixtral_v0.1) and is designed to carry out zero-shot classification.


## Model Overview

- **Model Type**: ModernBERT-large (BERT variant)
- **Task**: Zero-shot Classification
- **Languages**: English
- **Dataset**: [MoritzLaurer/synthetic_zeroshot_mixtral_v0.1](https://huggingface.co/datasets/MoritzLaurer/synthetic_zeroshot_mixtral_v0.1)
- **Fine-Tuning**: Fine-tuned for Zero-shot Classification

## Performance Metrics

To be added.

- **Training Loss**: Measures the model's fit to the training data.
- **Validation Loss**: Measures the model's generalization to unseen data.
- **Accuracy**: The percentage of correct predictions over all examples.
- **F1 Score**: A balanced metric between precision and recall.


## Installation and Example Usage

```bash
pip install transformers torch datasets
```
```python
classifier = pipeline("zero-shot-classification", "r-f/ModernBERT-large-zeroshot-v1")
sequence_to_classify = "I want to be an actor."
candidate_labels = ["space", "economy", "entertainment"]
output = classifier(sequence_to_classify, candidate_labels, multi_label=False)
print(output)
>>{'sequence': 'I want to be an actor.', 'labels': ['entertainment', 'space', 'economy'], 'scores': [0.9614731073379517, 0.028852475807070732, 0.009674412198364735]}
```

## Model Card

- **Model Name**: ModernBERT-large-zeroshot-v1
- **Hugging Face Repo**: [r-f/ModernBERT-large-zeroshot-v1](https://huggingface.co/rob-field1/ModernBERT-large-zeroshot-v1)
- **License**: MIT (or another applicable license)
- **Date**: 23-12-2024

## Training Details

- **Model**: ModernBERT (Large variant)
- **Framework**: PyTorch
- **Batch Size**: 32
- **Learning Rate**: 2e-5
- **Optimizer**: AdamW
- **Hardware**: RTX 4090

## Acknowledgments

- The model was trained on the [MoritzLaurer/synthetic_zeroshot_mixtral_v0.1](https://huggingface.co/datasets/MoritzLaurer/synthetic_zeroshot_mixtral_v0.1). And the training script was adapted from [MoritzLaurer/zeroshot-classifier](https://github.com/MoritzLaurer/zeroshot-classifier)
- Special thanks to the Hugging Face community and all contributors to the transformers library.

## License

This model is licensed under the MIT License. See the LICENSE file for more details.