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whisper-small-ft-balbus-sep28k-multiclass_v3a
b-brave/whisper-small-ft-balbus-sep28k-multiclass_v3a
whisper-small-ft-balbus-sep28k-multiclass_v3a is a audio classification model from b-brave. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- May 13, 2025
- Updated
- May 13, 2025
- SHA
- e9a7b8c8
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
whisper-small-ft-balbus-sep28k-multiclass_v3b
This model is a fine-tuned version of openai/whisper-small on the Apple dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.4681
- Accuracy: 0.655
- Precision: 0.7027
- Recall: 0.6335
- F1: 0.6299
- Roc-auc: None
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.5
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc-auc |
|---|---|---|---|---|---|---|---|---|
| 0.8055 | 0.2734 | 100 | 0.7699 | 0.3638 | 0.1213 | 0.3333 | 0.1779 | None |
| 0.7434 | 0.5468 | 200 | 0.7339 | 0.4385 | 0.2928 | 0.4117 | 0.3400 | None |
| 0.6728 | 0.8202 | 300 | 0.6096 | 0.5523 | 0.6058 | 0.5276 | 0.5052 | None |
| 0.4928 | 1.0936 | 400 | 0.5101 | 0.6362 | 0.6856 | 0.6166 | 0.6175 | None |
| 0.4613 | 1.3671 | 500 | 0.4971 | 0.6262 | 0.7070 | 0.6003 | 0.5895 | None |
| 0.4563 | 1.6405 | 600 | 0.4731 | 0.6642 | 0.6937 | 0.6475 | 0.6498 | None |
| 0.449 | 1.9139 | 700 | 0.4681 | 0.655 | 0.7027 | 0.6335 | 0.6299 | None |
Framework versions
- Transformers 4.45.2
- Pytorch 2.2.0
- Datasets 3.6.0
- Tokenizers 0.20.3
- Task
- Audio Classification
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- May 13, 2025
- Updated
- May 13, 2025