---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- 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: 0.9816122388937923
---

<!-- 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: 0.0866
- Accuracy: 0.9816

## 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: 32
- eval_batch_size: 32
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4888        | 1.0   | 384  | 0.3631          | 0.9701   |
| 0.2033        | 2.0   | 768  | 0.1407          | 0.9721   |
| 0.1843        | 3.0   | 1152 | 0.1012          | 0.9782   |
| 0.1435        | 4.0   | 1537 | 0.0895          | 0.9807   |
| 0.116         | 5.0   | 1920 | 0.0866          | 0.9816   |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2