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license: apache-2.0
language: en
tags:
- temporal
- time-module
- pieces
- intent-classification
- temporal-intent
datasets:
- Pieces/temporal-intent-classification-dataset-split
base_model: google/flan-t5-small
metrics:
- accuracy
- f1
pipeline_tag: text-classification
---
# TIME-Module: Classification — flan-t5-small
## Model Description
Temporal intent classification model trained on the split dataset. Classifies user queries into 6 temporal intent categories: Action Scheduling, Content Retrieval, Current Status, Future Information/Planning, Non-Temporal, and Temporal - General.
## Training Details
- **Base Model:** [google/flan-t5-small](https://huggingface.co/google/flan-t5-small)
- **Architecture:** T5ForSequenceClassification
- **Dataset:** [Pieces/temporal-intent-classification-dataset-split](https://huggingface.co/datasets/Pieces/temporal-intent-classification-dataset-split) (15,488 train / 1,721 val / 4,303 test)
- **Training Steps:** 17,500
- **Learning Rate:** 3e-4
- **Batch Size:** 64 × 2
- **Mixed Precision:** bf16
- **Hardware:** NVIDIA RTX 4090 (24 GB)
## Results
| Metric | Value |
|--------|-------|
| accuracy | 95.91% |
| f1_weighted | ~95.9% |
## Usage
```python
from transformers import pipeline
pipe = pipeline('text-classification', model='Pieces/time-classification-flan-t5-small-split-best')
result = pipe('What meetings do I have tomorrow?')
```
## Part of the TIME-Module Project
This model is part of the TIME (Temporal Intent, Mapping, and Extraction) module, a suite of models for understanding and processing temporal information in natural language.
**Related models:**
- [Pieces/time-classification-flan-t5-small-split-best](https://huggingface.co/Pieces/time-classification-flan-t5-small-split-best) — Intent classification
- [Pieces/time-mapping-flan-t5-small-quality-best](https://huggingface.co/Pieces/time-mapping-flan-t5-small-quality-best) — Span prediction (best)
- [Pieces/time-mapping-t5gemma-270m-best](https://huggingface.co/Pieces/time-mapping-t5gemma-270m-best) — Span prediction (T5Gemma)
## Citation
```bibtex
@software{time_module,
title={TIME-Module: Temporal Intent, Mapping, and Extraction},
author={Pieces},
year={2026},
url={https://huggingface.co/Pieces}
}
```
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