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distil-large-v2_ADReSSo
giyong/distil-large-v2_ADReSSo
distil-large-v2_ADReSSo is a audio classification model from giyong. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- mit
- Model type
- whisper
- Access
- Public
- Created
- May 3, 2025
- Updated
- May 3, 2025
- SHA
- debe33d9
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. -->
distil-large-v2_ADReSSo
This model is a fine-tuned version of distil-whisper/distil-large-v2 on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.7772
- Accuracy: 0.7606
- F1: 0.7733
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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7 | 1.0 | 16 | 0.6865 | 0.5714 | 0.25 |
| 0.6796 | 2.0 | 32 | 0.6753 | 0.5 | 0.0 |
| 0.5951 | 3.0 | 48 | 0.5741 | 0.6905 | 0.6667 |
| 0.3828 | 4.0 | 64 | 1.2909 | 0.5476 | 0.24 |
| 0.1822 | 5.0 | 80 | 1.0336 | 0.7857 | 0.7907 |
| 0.2948 | 6.0 | 96 | 0.9771 | 0.7619 | 0.7222 |
| 0.064 | 7.0 | 112 | 0.9788 | 0.8333 | 0.8293 |
| 0.0007 | 8.0 | 128 | 1.0079 | 0.8333 | 0.8444 |
| 0.0003 | 9.0 | 144 | 1.0393 | 0.8333 | 0.8444 |
| 0.0002 | 10.0 | 160 | 1.0977 | 0.8571 | 0.8696 |
| 0.0001 | 11.0 | 176 | 1.1214 | 0.8571 | 0.8696 |
| 0.0001 | 12.0 | 192 | 1.1597 | 0.8571 | 0.8696 |
| 0.0001 | 13.0 | 208 | 1.1867 | 0.8571 | 0.8696 |
| 0.0001 | 14.0 | 224 | 1.2124 | 0.8571 | 0.8696 |
| 0.0001 | 15.0 | 240 | 1.2319 | 0.8571 | 0.8696 |
| 0.0001 | 16.0 | 256 | 1.2440 | 0.8571 | 0.8696 |
| 0.0001 | 17.0 | 272 | 1.2629 | 0.8571 | 0.8696 |
| 0.0001 | 18.0 | 288 | 1.2777 | 0.8571 | 0.8696 |
| 0.0001 | 19.0 | 304 | 1.2876 | 0.8571 | 0.8696 |
| 0.0 | 20.0 | 320 | 1.3026 | 0.8571 | 0.8696 |
| 0.0 | 21.0 | 336 | 1.3156 | 0.8571 | 0.8696 |
| 0.0 | 22.0 | 352 | 1.3261 | 0.8571 | 0.8696 |
| 0.0 | 23.0 | 368 | 1.3362 | 0.8571 | 0.8696 |
| 0.0 | 24.0 | 384 | 1.3445 | 0.8571 | 0.8696 |
| 0.0 | 25.0 | 400 | 1.3532 | 0.8571 | 0.8696 |
| 0.0 | 26.0 | 416 | 1.3604 | 0.8571 | 0.8696 |
| 0.0 | 27.0 | 432 | 1.3673 | 0.8571 | 0.8696 |
| 0.0 | 28.0 | 448 | 1.3746 | 0.8571 | 0.8696 |
| 0.0 | 29.0 | 464 | 1.3809 | 0.8571 | 0.8696 |
| 0.0 | 30.0 | 480 | 1.3878 | 0.8571 | 0.8696 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.5.0+cu118
- Datasets 2.14.6
- Tokenizers 0.21.1
- Task
- Audio Classification
- Library
- transformers
- Type
- whisper
- License
- mit
- Created
- May 3, 2025
- Updated
- May 3, 2025