metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: wav2vec2-base-ft-keyword-spotting
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: superb
type: superb
config: ks
split: validation
args: ks
metrics:
- name: Accuracy
type: accuracy
value: 0.9763165636952045
wav2vec2-base-ft-keyword-spotting
This model is a fine-tuned version of facebook/wav2vec2-base on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 0.4062
- Accuracy: 0.9763
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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: 8.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8801 | 0.9962 | 199 | 1.7454 | 0.6209 |
| 1.389 | 1.9962 | 398 | 1.2404 | 0.6518 |
| 1.1239 | 2.9962 | 597 | 1.0690 | 0.7880 |
| 0.9107 | 3.9962 | 796 | 0.7700 | 0.8961 |
| 0.7231 | 4.9962 | 995 | 0.6167 | 0.9659 |
| 0.5972 | 5.9962 | 1194 | 0.4838 | 0.9735 |
| 0.5143 | 6.9962 | 1393 | 0.4227 | 0.9762 |
| 0.5159 | 7.9962 | 1592 | 0.4062 | 0.9763 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.3.1
- Tokenizers 0.21.0