lora-green-patents

Model Card for aslan-ng/lora-green-patents

This model classifies patents and product descriptions as green (eco-friendly) or not green. It was finetuned with LoRA on a binary text dataset of patent descriptions.

Model Details

Model Description

• Developed by: Jennifer Evans, Aslan Noorghasemi
• Model type: Text classifier (binary classification)
• Languages (NLP): English
• Finetuned from model: LoRA with the "distilbert-base-uncased" model and DistilBertForSequenceClassification

Model Sources

• Training Dataset: https://huggingface.co/datasets/cwinkler/patents_green_plastics
• Model Details
• Train/test split: 80/20
• LoRA alpha: 16
• LoRA dropout: 0.1
• Eval steps: 500
• Learning rate: 2e-4
• Training epochs: 10

Uses

Direct Use

Use this model to classify whether input text is considered green (eco-friendly) or not. It takes patent or product descriptions as text inputs and returns a predicted binary label and probabilities.

Downstream Use

It can be incorporated into larger text evaluation systems (ie. patent and product analysis tasks) as a pre-screening classifier.

Out-of-Scope Use

Not intended for:

• Safety-critical deployment without further validation.
• Identifying other labels beyond green / not green.
• Applications outside of evaluating patent and product descriptions.

Bias, Risks, and Limitations

The model is trained on a specific dataset. It may:

• Misclassify unusual or unclear eco-friendly descriptions.
• Perform poorly on non-U.S. descriptions if not present in training.
• Inherit any biases in the training text.

Recommendations

Always test on your target data before deployment. Combine with additional checks in safety-critical scenarios.

How to Get Started with the Model

The model can be used by loading both the base and adaptor

• Model Name: "distilbert-base-uncased"
• Tokenizer: AutoTokenizer.from_pretrained(REPO_ID_LORA_GREEN_PATENTS)
• Base Model: AutoModelForSequenceClassification.from_pretrained(model_name, num_labels=2)
• Model: PeftModel.from_pretrained(base_model, REPO_ID_LORA_GREEN_PATENTS)