MHSA-Word-Model/README.md

Multi-Head Self-Attention (Vaswani 2017)

CRNN with Transformer-style Multi-Head Self-Attention between BiLSTM layers 2 and 3.

Architecture

• Family: MHSA
• CNN backbone: 6 convolutional blocks (max 256 channels)
• Recurrent block: 3 BiLSTM layers, hidden = 160 per direction
• Decoding: Connectionist Temporal Classification (CTC)
• Parameters: 4,044,625

Test Performance (DASTNUS, seed 42)

Metric	Value
Test CER	0.0383
Test WER	0.1655

Files

• model.safetensors — model weights
• config.json — architecture and training configuration
• vocab.json — character-to-index mapping (CTC blank at index 0)
• idx_to_char.json — reverse mapping for decoding

License

Released for non-commercial scientific research purposes only.