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

<!-- 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. -->

# w2v2-ks-jpqd-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: 0.0641
- Accuracy: 0.9815

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 64
- 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: 0.1
- num_epochs: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4606        | 1.0   | 399  | 0.1543          | 0.9723   |
| 14.8746       | 2.0   | 798  | 14.9490         | 0.9681   |
| 24.7043       | 3.0   | 1197 | 24.6662         | 0.9706   |
| 30.626        | 4.0   | 1596 | 30.4279         | 0.9732   |
| 33.4796       | 5.0   | 1995 | 33.3182         | 0.9750   |
| 34.4405       | 6.0   | 2394 | 34.2327         | 0.9744   |
| 34.1743       | 7.0   | 2793 | 34.0161         | 0.9741   |
| 33.47         | 8.0   | 3192 | 33.2669         | 0.9748   |
| 0.2278        | 9.0   | 3591 | 0.1125          | 0.9757   |
| 0.2259        | 10.0  | 3990 | 0.0848          | 0.9778   |
| 0.1629        | 11.0  | 4389 | 0.0734          | 0.9788   |
| 0.1658        | 12.0  | 4788 | 0.0736          | 0.9803   |
| 0.2264        | 13.0  | 5187 | 0.0658          | 0.9803   |
| 0.1564        | 14.0  | 5586 | 0.0677          | 0.9819   |
| 0.1716        | 15.0  | 5985 | 0.0641          | 0.9815   |


### Framework versions

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