---
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: w2v2-ks-jpqd-quant-FE-finetuned-student
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v2-ks-jpqd-quant-FE-finetuned-student

This model is a fine-tuned version of [anton-l/wav2vec2-base-ft-keyword-spotting](https://huggingface.co/anton-l/wav2vec2-base-ft-keyword-spotting) on the superb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0869
- Accuracy: 0.9794

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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: 0.5
- num_epochs: 12.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3477        | 1.0   | 399  | 0.1516          | 0.9637   |
| 5.5957        | 2.0   | 798  | 5.4798          | 0.9545   |
| 8.7806        | 3.0   | 1197 | 8.6491          | 0.9634   |
| 10.4524       | 4.0   | 1596 | 10.2701         | 0.9554   |
| 10.8964       | 5.0   | 1995 | 10.7809         | 0.9647   |
| 10.9322       | 6.0   | 2394 | 10.7806         | 0.9619   |
| 0.2389        | 7.0   | 2793 | 0.1148          | 0.9738   |
| 0.2522        | 8.0   | 3192 | 0.1013          | 0.9747   |
| 0.2213        | 9.0   | 3591 | 0.0983          | 0.9754   |
| 0.2053        | 10.0  | 3990 | 0.0934          | 0.9768   |
| 0.1543        | 11.0  | 4389 | 0.0875          | 0.9779   |
| 0.1836        | 12.0  | 4788 | 0.0869          | 0.9794   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2