File size: 897 Bytes
957cd6d 513e1a2 957cd6d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 |
---
datasets:
- leonvanbokhorst/topic-drift
---
# Topic Drift Detector Model
## Version: v20241225_085248
This model detects topic drift in conversations using an enhanced attention-based architecture.
## Model Architecture
- Multi-head attention mechanism
- Bidirectional LSTM for pattern detection
- Dynamic weight generation
- Semantic bridge detection
## Performance Metrics
```txt
=== Full Training Results ===
Best Validation RMSE: 0.0107
Best Validation R²: 0.8867
=== Test Set Results ===
Loss: 0.0002
RMSE: 0.0129
R²: 0.8373
```
## Training Curves
## Usage
```python
import torch
# Load model
model = torch.load('models/v20241225_085248/topic_drift_model.pt')
# Use model for inference
# Input shape: [batch_size, sequence_length * embedding_dim]
# Output shape: [batch_size, 1] (drift score between 0 and 1)
``` |