---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast-finetuned-speech-commands-v2-finetuned
  results: []
datasets:
- mazkooleg/0-9up_google_speech_commands_augmented_raw
---

<!-- 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. -->

# ast-finetuned-speech-commands-v2-finetuned

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0210
- Accuracy: 0.9979

## 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: 1e-07
- 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: 5

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.1781        | 1.0   | 8558  | 0.9970   | 0.1609          |
| 0.0217        | 2.0   | 17116 | 0.9979   | 0.0210          |
| 0.018         | 3.0   | 25674 | 0.9979   | 0.0144          |
| 0.0215        | 4.0   | 34232 | 0.9976   | 0.0129          |
| 0.0407        | 5.0   | 42790 | 0.9976   | 0.0126          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.11.0+cpu
- Datasets 2.10.0
- Tokenizers 0.12.1