
![LLM_IMAGE](img.jpeg)

# neural-chat-finetuned-bilic-v1

This model is a fine-tuned version of [Intel/neural-chat-7b-v3-1](https://huggingface.co/Intel/neural-chat-7b-v3-1) on our custom dataset.

## Model description

This is a fine tuned version of the intel's Neuralchat model, specifically trained on a carefully curated dataset on fraud detection. We implemented a contextual based architecture to enable the model learn and be adept at understanding context within a conversation as opposed to the traditional rule based approach.
## Intended uses & limitations

- detecting fraudulent conversations in real-time
- Giving a summary of conversations and suggestions
- Understanding with high accuracy the context in a conversation to make better predictions

## Training

 50,000 synthetically conversations


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 250
- mixed_precision_training: Native AMP


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "Intel/neural-chat-7b-v3-1", "model-index": [{"name": "neural-chat-finetuned-bilic-v1", "results": []}]}
transformers pytorch tensorboard safetensors mistral text-generation generated_from_trainer base_model:Intel/neural-chat-7b-v3-1 license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us