Genre Identification Baseline

--- license: mit library_name: pytorch tags: - audio-classification - music-genre-classification - pytorch - librosa --- # Genre Identification Deep Checkpoints Deep music genre identification checkpoints exported from the IITM DL & GenAI project. ## Summary - Version: `V16` - Live Space inference: `ResNet50 + EfficientNet-B4 + EfficientNet-B3 ensemble on mel-spectrogram heatmaps` - Primary notebook reference: `notebooks/dl-21f2000735-notebook-t12026 (12).ipynb` - Feature pipeline: `30s audio -> mel256 spectrogram image -> ResNet50/EfficientNet ensemble` - Tracked public leaderboard score: `0.23380` ## Labels - `0` -> `blues` - `1` -> `classical` - `2` -> `country` - `3` -> `disco` - `4` -> `hiphop` - `5` -> `jazz` - `6` -> `metal` - `7` -> `pop` - `8` -> `reggae` - `9` -> `rock` ## Local demo predictions - `demo_audio_pairs/auto_sample/original.wav` -> **classical** - `demo_audio_pairs/auto_sample/messy.wav` -> **classical** ## Files - `deep_models/efficientnet_b4_best_2.pth`: main CNN checkpoint used by the Space - `deep_models/efficientnet_b3_best_2.pth`: secondary CNN checkpoint used by the Space - `deep_models/resnet50_best_2.pth`: additional CNN checkpoint used by the Space - `artifacts/rf_baseline_best_public_summary.json`: local validation summary ## Usage Use this model repo with the companion Hugging Face Space. The live demo loads the ResNet50, EfficientNet-B4, and EfficientNet-B3 checkpoints from `deep_models/`.

Source context: 0 downloads · 0 likes · Pipeline audio-classification · Library pytorch · Repo Jating4you/genre-identification-baseline