---
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
base_model: openai/whisper-small
model-index:
- name: whisper-small-keyword-spotting
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-small-keyword-spotting

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the kw-spotting-fsc-sl-agv dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0183
- Accuracy: 0.9998

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0268        | 1.0   | 318  | 0.0720          | 0.9685   |
| 0.0195        | 2.0   | 637  | 0.0183          | 0.9998   |
| 0.0111        | 3.0   | 956  | 0.2009          | 0.9168   |
| 0.0065        | 4.0   | 1275 | 0.2847          | 0.8544   |
| 0.0086        | 4.99  | 1590 | 0.1895          | 0.9168   |


### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2