---
language:
  - hi
  - en
license: apache-2.0
tags:
  - hindi
  - hinglish
  - song-lyrics
  - music-classification
  - multimodal
base_model: AkshitaS/bhasha-embed-v0
---

# meet_models: Hindi song theme classification

**How to access and run the models: see [`HOW_TO_USE.md`](HOW_TO_USE.md).** Quick start:

```bash
huggingface-cli login
huggingface-cli download meet5568/meet_models --local-dir meet_models
cd meet_models/code && pip install -r requirements.txt
python predict.py --model-dir .. --lyrics "tujhe dekha toh yeh jaana sanam"
```

All models of the project *Multimodal Thematic Classification and Generational Analysis of Hindi
Songs*: classifying Hindi film songs as romance, sadness, celebration or motivational from their
lyrics, singing voice and music.

```
lyrics_encoder/
  tsdae/                       BhashaEmbed adapted to song lyrics with TSDAE (no labels)
  theme_tuned/fold_0 ... 4/    + triplet fine-tuning on the four themes, one encoder per CV fold
  theme_tuned/training_summary.json, training_log.json
classification/
  <combination>/fold_<k>/      chosen classifier per input combination and fold (75)
  index.csv, README.md
code/                          predict.py (run the models), classify.py (model definitions),
                               config.yaml, save_models.py, requirements.txt
HOW_TO_USE.md                  access, download, run
```

## Results (5-fold cross-validated test macro-F1; 0.25 = chance)
| input | macro-F1 |
|---|---|
| audio only (vocal + instrument + mix) | 0.513 |
| lyrics, TSDAE encoder | 0.612 |
| lyrics, theme-tuned encoder | 0.682 |
| lyrics + instrument + mix (best) | 0.699 |
| average of the 8 lyrics-based models | 0.705 |

**Important:** encoder `theme_tuned/fold_k` and classifiers `fold_k` were trained without the songs of
test fold k. Use the fold-k models only to evaluate on fold k; for new songs, average the predictions
of the five folds.

Base model: [AkshitaS/bhasha-embed-v0](https://huggingface.co/AkshitaS/bhasha-embed-v0) (MuRIL-based,
Devanagari Hindi, romanized Hindi and English). Full description: the project report.