| | --- |
| | 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: 0.9826419535157399 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # wav2vec2-base-ft-keyword-spotting |
| |
|
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0954 |
| | - Accuracy: 0.9826 |
| |
|
| | ## 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: 48 |
| | - eval_batch_size: 32 |
| | - seed: 0 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 192 |
| | - 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 | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 1.3624 | 1.0 | 267 | 1.1959 | 0.6546 | |
| | | 0.3854 | 2.0 | 534 | 0.2675 | 0.9734 | |
| | | 0.2473 | 3.0 | 801 | 0.1461 | 0.9768 | |
| | | 0.1997 | 4.0 | 1068 | 0.1088 | 0.9804 | |
| | | 0.1723 | 5.0 | 1335 | 0.0954 | 0.9826 | |
| | | 0.1442 | 6.0 | 1602 | 0.0927 | 0.9813 | |
| | | 0.1397 | 7.0 | 1869 | 0.0892 | 0.9812 | |
| | | 0.1368 | 7.9728 | 2128 | 0.0896 | 0.9812 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.49.0 |
| | - Pytorch 2.6.0+cu118 |
| | - Datasets 3.3.1 |
| | - Tokenizers 0.21.0 |
| |
|
