Text Classification
Transformers
Safetensors
English
roberta
record-types
data-licensing
company-data
data-export
text-embeddings-inference
Instructions to use aitrainingdatabroker/record-type-page-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aitrainingdatabroker/record-type-page-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aitrainingdatabroker/record-type-page-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aitrainingdatabroker/record-type-page-classifier") model = AutoModelForSequenceClassification.from_pretrained("aitrainingdatabroker/record-type-page-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add README.md
Browse files
README.md
ADDED
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---
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license: apache-2.0
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language:
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- en
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library_name: transformers
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pipeline_tag: text-classification
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base_model: distilroberta-base
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datasets:
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- aitrainingdatabroker/company-record-types-and-limits
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- aitrainingdatabroker/company-data-licensing-faq-by-topic
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tags:
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- record-types
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- data-licensing
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- text-classification
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- company-data
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- data-export
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---
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# Record Type Page Classifier
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Reads a passage about company records and says which of 33 record types it is most likely about: support tickets, team chat, CRM history, CAD files, tool exports such as Slack or Jira, and more.
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All training text is our own, from pages published at aitrainingdatabroker.com. Nothing comes from a customer.
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Related tool: [company-record-types-and-limits-finder](https://huggingface.co/spaces/aitrainingdatabroker/company-record-types-and-limits-finder) (a Space that runs in your browser).
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## Why it exists
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Before data is prepared, a team has to say what kind of record each file is. This model suggests the record type for a passage so a person can confirm it.
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## Use it
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```python
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from transformers import pipeline
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classify = pipeline("text-classification", model="aitrainingdatabroker/record-type-page-classifier", top_k=3)
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print(classify("A Jira export with issue keys, comments, status changes and linked pull requests."))
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```
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## How it was trained
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Fine-tuned from `distilroberta-base` for 25 epochs on one RTX 3070. Training data: 419 passages from [company-record-types-and-limits](https://huggingface.co/datasets/aitrainingdatabroker/company-record-types-and-limits), [company-data-licensing-faq-by-topic](https://huggingface.co/datasets/aitrainingdatabroker/company-data-licensing-faq-by-topic), which are our own published page text. It was trained on item descriptions, introductions and section paragraphs from our 33 record-type pages and tested on the questions and answers of those pages, which it never saw in training. The scripts that built the data and trained the model are in `source/`; the full scores are in `scores.json`.
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## Test scores
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On 107 held-out rows: accuracy 0.533, macro F1 0.497.
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| Label | F1 | Count |
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|---|---|---|
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| `accounting-and-erp-records` | 0.0 | 3 |
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| `cad-and-engineering-files` | 0.8 | 3 |
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| `call-recordings` | 0.571 | 3 |
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| `change-orders-and-rfis` | 0.8 | 3 |
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| `claims-and-underwriting-files` | 0.5 | 3 |
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| `client-deliverables-and-drafts` | 0.4 | 3 |
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| `closed-deal-files` | 0.5 | 3 |
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| `code-and-pull-request-history` | 0.0 | 3 |
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| `confluence-data-export` | 0.889 | 4 |
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| `consented-recordings` | 0.667 | 3 |
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| `crm-history` | 0.5 | 3 |
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| `egocentric-video` | 0.857 | 4 |
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| `github-repository-export` | 0.444 | 3 |
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| `gmail-data-export` | 0.0 | 4 |
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| `google-drive-export` | 0.462 | 3 |
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| `hubspot-data-export` | 0.286 | 3 |
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| `inspection-reports-and-photos` | 0.857 | 3 |
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| `jira-data-export` | 0.333 | 3 |
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| `lab-notebooks-and-experiment-records` | 0.667 | 3 |
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| `labeled-tables-and-datasets` | 1.0 | 4 |
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| `microsoft-365-email-export` | 0.364 | 3 |
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| `native-word-excel-and-powerpoint-files` | 0.4 | 4 |
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| `project-and-task-history` | 0.5 | 3 |
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| `quickbooks-data-export` | 0.4 | 3 |
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| `quotes-and-estimates` | 0.667 | 3 |
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| `salesforce-data-export` | 0.0 | 4 |
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| `slack-data-export` | 0.727 | 4 |
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| `sops-and-knowledge-bases` | 0.667 | 3 |
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| `support-tickets` | 0.571 | 3 |
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| `team-chat` | 0.0 | 3 |
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| `theses-and-dissertations` | 0.667 | 4 |
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| `work-orders-and-dispatch-notes` | 0.5 | 3 |
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| `zendesk-data-export` | 0.4 | 3 |
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## Limits
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- 33 classes with about 13 training passages each, and several are close neighbours (the export guides especially), so treat the top three as candidates.
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- Trained on one broker's page text.
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- This model is not legal advice and not a certification. A person should review its output before anything is shared or decided, and your counsel decides what a rule requires.
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## Read more
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- [Record types and export guides](https://aitrainingdatabroker.com/data/?utm_source=huggingface&utm_medium=model&utm_campaign=record-type-page-classifier)
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- [Can you license CRM history to AI?](https://aitrainingdatabroker.com/data/crm-history/?utm_source=huggingface&utm_medium=model&utm_campaign=record-type-page-classifier)
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- [Jira data export for AI licensing](https://aitrainingdatabroker.com/data/jira-data-export/?utm_source=huggingface&utm_medium=model&utm_campaign=record-type-page-classifier)
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## License and credit
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Apache 2.0. Please credit **AI Training Data Broker** and link to https://aitrainingdatabroker.com/ when you share or build on it.
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## About
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AI Training Data Broker is a broker and technical advisor for companies that sell or license their data to AI labs. It guides the technical side, including export, format, de-identification and compliance, and publishes free guides, checklists and tools.
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