| --- |
| language: |
| - en |
| license: apache-2.0 |
| tags: |
| - insurance |
| - document-classification |
| - modernbert |
| - uk-insurance |
| - text-classification |
| - bytical |
| library_name: transformers |
| pipeline_tag: text-classification |
| base_model: answerdotai/ModernBERT-base |
| datasets: |
| - piyushptiwari/insureos-training-data |
| model-index: |
| - name: InsureDocClassifier |
| results: |
| - task: |
| type: text-classification |
| name: Insurance Document Classification |
| metrics: |
| - type: f1 |
| value: 1.0 |
| name: F1 (macro) |
| - type: accuracy |
| value: 1.0 |
| name: Accuracy |
| --- |
| |
| # InsureDocClassifier β Insurance Document Classification |
|
|
| **Created by [Bytical AI](https://bytical.ai)** β AI agents that run insurance operations. |
|
|
| ## Model Description |
|
|
| InsureDocClassifier is a 12-class insurance document classifier built on ModernBERT-base. It automatically categorizes insurance documents into their correct type, enabling automated document routing, indexing, and processing in insurance operations. |
|
|
| ### Document Classes (12) |
|
|
| | ID | Document Type | Description | |
| |----|--------------|-------------| |
| | 0 | Policy Schedule | Policy details and coverage summary | |
| | 1 | Certificate of Insurance | Proof of insurance document | |
| | 2 | Claim Form | Insurance claim submission form | |
| | 3 | Loss Adjuster Report | Assessment report from loss adjuster | |
| | 4 | Bordereaux β Premium | Premium transaction records | |
| | 5 | Bordereaux β Claims | Claims transaction records | |
| | 6 | Endorsement | Policy amendment document | |
| | 7 | Renewal Notice | Policy renewal notification | |
| | 8 | Statement of Fact | Declaration of material facts | |
| | 9 | FNOL Report | First Notification of Loss report | |
| | 10 | Subrogation Notice | Recovery rights notification | |
| | 11 | Policy Wording | Full policy terms and conditions | |
|
|
| ### Training Details |
|
|
| | Parameter | Value | |
| |-----------|-------| |
| | Base Model | answerdotai/ModernBERT-base | |
| | Training Samples | 10,000 synthetic insurance documents | |
| | Epochs | 5 | |
| | Eval Loss | 4.17e-06 | |
| | GPU | NVIDIA Tesla T4 16GB | |
|
|
| ### Evaluation Results |
|
|
| | Metric | Score | |
| |--------|-------| |
| | **Accuracy** | **1.0** | |
| | **F1 (macro)** | **1.0** | |
| | **F1 (weighted)** | **1.0** | |
| | Eval Samples/sec | 32.96 | |
|
|
| ## How to Use |
|
|
| ```python |
| from transformers import AutoModelForSequenceClassification, AutoTokenizer |
| |
| model = AutoModelForSequenceClassification.from_pretrained("piyushptiwari/InsureDocClassifier") |
| tokenizer = AutoTokenizer.from_pretrained("piyushptiwari/InsureDocClassifier") |
| |
| text = "We hereby confirm that the above-named insured holds a valid policy of insurance..." |
| inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512) |
| outputs = model(**inputs) |
| predicted_class = outputs.logits.argmax(-1).item() |
| |
| labels = { |
| 0: "Policy Schedule", 1: "Certificate of Insurance", 2: "Claim Form", |
| 3: "Loss Adjuster Report", 4: "Bordereaux β Premium", 5: "Bordereaux β Claims", |
| 6: "Endorsement", 7: "Renewal Notice", 8: "Statement of Fact", |
| 9: "FNOL Report", 10: "Subrogation Notice", 11: "Policy Wording" |
| } |
| print(f"Document type: {labels[predicted_class]}") |
| ``` |
|
|
| ## Part of the INSUREOS Model Suite |
|
|
| This model is part of the **INSUREOS** β a complete AI/ML suite for insurance operations built by Bytical AI: |
|
|
| | Model | Task | Metric | |
| |-------|------|--------| |
| | [InsureLLM-4B](https://huggingface.co/piyushptiwari/InsureLLM-4B) | Insurance domain LLM | ROUGE-1: 0.384 | |
| | **InsureDocClassifier** (this model) | 12-class document classification | F1: 1.0 | |
| | [InsureNER](https://huggingface.co/piyushptiwari/InsureNER) | 13-entity Named Entity Recognition | F1: 1.0 | |
| | [InsureFraudNet](https://huggingface.co/piyushptiwari/InsureFraudNet) | Fraud detection (Motor/Property/Liability) | AUC-ROC: 1.0 | |
| | [InsurePricing](https://huggingface.co/piyushptiwari/InsurePricing) | Insurance pricing (GLM + EBM) | MAE: Β£11,132 | |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{bytical2026insuredocclassifier, |
| title={InsureDocClassifier: Insurance Document Classification with ModernBERT}, |
| author={Bytical AI}, |
| year={2026}, |
| url={https://huggingface.co/piyushptiwari/InsureDocClassifier} |
| } |
| ``` |
|
|
| ## About Bytical AI |
|
|
| [Bytical](https://bytical.ai) builds AI agents that run insurance operations β claims automation, underwriting intelligence, digital sales, and core system modernization for insurers across the UK and Europe. Microsoft AI Partner | NVIDIA | Salesforce. |
|
|