---
license: bsd-3-clause
base_model: MIT/ast-finetuned-speech-commands-v2
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: audio-commands
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: speech_commands
      type: speech_commands
      config: v0.03
      split: test
      args: v0.03
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9256316218418907
---

<!-- 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. -->

# audio-commands

This model is a fine-tuned version of [MIT/ast-finetuned-speech-commands-v2](https://huggingface.co/MIT/ast-finetuned-speech-commands-v2) on the speech_commands dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3977
- Accuracy: 0.9256

## 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: 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0581        | 1.0   | 663   | 0.4816          | 0.8975   |
| 0.0454        | 2.0   | 1326  | 0.4184          | 0.9024   |
| 0.0404        | 3.0   | 1989  | 0.4361          | 0.9010   |
| 0.025         | 4.0   | 2653  | 0.4368          | 0.9016   |
| 0.0169        | 5.0   | 3316  | 0.3692          | 0.9173   |
| 0.0173        | 6.0   | 3979  | 0.4131          | 0.9173   |
| 0.0096        | 7.0   | 4642  | 0.3800          | 0.9177   |
| 0.0022        | 8.0   | 5306  | 0.3535          | 0.9264   |
| 0.0031        | 9.0   | 5969  | 0.3241          | 0.9315   |
| 0.0008        | 10.0  | 6632  | 0.3697          | 0.9236   |
| 0.0002        | 11.0  | 7295  | 0.4189          | 0.9173   |
| 0.001         | 12.0  | 7959  | 0.3206          | 0.9287   |
| 0.0003        | 13.0  | 8622  | 0.3794          | 0.9205   |
| 0.0003        | 14.0  | 9285  | 0.3999          | 0.9199   |
| 0.0           | 15.0  | 9948  | 0.4002          | 0.9220   |
| 0.0           | 16.0  | 10612 | 0.3896          | 0.9248   |
| 0.0001        | 17.0  | 11275 | 0.3930          | 0.9248   |
| 0.0           | 18.0  | 11938 | 0.3952          | 0.9254   |
| 0.0           | 19.0  | 12601 | 0.3971          | 0.9254   |
| 0.0           | 19.99 | 13260 | 0.3977          | 0.9256   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2