Instructions to use fruzti/wav2vec2-base-100k-voxpopuli-finetuned-minds with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fruzti/wav2vec2-base-100k-voxpopuli-finetuned-minds with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="fruzti/wav2vec2-base-100k-voxpopuli-finetuned-minds")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("fruzti/wav2vec2-base-100k-voxpopuli-finetuned-minds") model = AutoModelForAudioClassification.from_pretrained("fruzti/wav2vec2-base-100k-voxpopuli-finetuned-minds") - Notebooks
- Google Colab
- Kaggle
wav2vec2-base-100k-voxpopuli-finetuned-minds
This model is a fine-tuned version of facebook/wav2vec2-base-100k-voxpopuli on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6483
- Accuracy: 0.0796
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.6425 | 1.0 | 57 | 2.6429 | 0.0442 |
| 2.6422 | 2.0 | 114 | 2.6458 | 0.0354 |
| 2.6434 | 3.0 | 171 | 2.6437 | 0.0531 |
| 2.6452 | 4.0 | 228 | 2.6485 | 0.0531 |
| 2.6256 | 5.0 | 285 | 2.6475 | 0.0531 |
| 2.6384 | 6.0 | 342 | 2.6489 | 0.0531 |
| 2.6259 | 7.0 | 399 | 2.6496 | 0.0354 |
| 2.645 | 8.0 | 456 | 2.6484 | 0.0531 |
| 2.6144 | 9.0 | 513 | 2.6482 | 0.0796 |
| 2.6338 | 10.0 | 570 | 2.6483 | 0.0796 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 3.6.0
- Tokenizers 0.22.1
- Downloads last month
- 6
Model tree for fruzti/wav2vec2-base-100k-voxpopuli-finetuned-minds
Base model
facebook/wav2vec2-base-100k-voxpopuli