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--- |
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license: mit |
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language: |
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- en |
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metrics: |
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- rouge |
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base_model: |
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- allenai/led-base-16384 |
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pipeline_tag: summarization |
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library_name: transformers |
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--- |
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# Longformer fine-tuned to summarize Terms of Service |
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Terms of Service documents are lengthy, complex, and time-consuming to read. Due to its vague language, people often don’t understand what they are agreeing to. Hence, we have fine-tuned Longformer model to help summarize TOS and make it easy to read and understand. |
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<br><br> |
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This model is a fine-tuned version of [`allenai/led-base-16384`](https://huggingface.co/allenai/led-base-16384) <br> |
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Dataset used: TL;DRLegal and TOS;DR website <br> |
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It achieves the following results on the validation set:<br> |
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* ROUGE-1: 0.28 |
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* ROUGE-2: 0.13 |
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* ROUGE-L: 0.27 |
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## How to Use |
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```python |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification |
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tokenizer = AutoTokenizer.from_pretrained("aarushi-211/TOS-Longformer") |
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model = AutoModelForSequenceClassification.from_pretrained("aarushi-211/TOS-Longformer") |
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inputs = tokenizer("Your input text here", return_tensors="pt", truncation=True) |
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outputs = model(**inputs) |
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logits = outputs.logits |
