---
library_name: transformers
license: apache-2.0
base_model: arbml/whisper-tiny-ar
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: whisper-tiny-ar-ft-kws-speech-commands
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Speech Commands
      type: speech_commands
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5204081632653061
---

<!-- 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. -->

# whisper-tiny-ar-ft-kws-speech-commands

This model is a fine-tuned version of [arbml/whisper-tiny-ar](https://huggingface.co/arbml/whisper-tiny-ar) on the Speech Commands dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8423
- Accuracy: 0.5204

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6826        | 1.0   | 1325  | 0.7084          | 0.4966   |
| 0.7052        | 2.0   | 2650  | 0.6965          | 0.5      |
| 0.7409        | 3.0   | 3975  | 0.6876          | 0.5510   |
| 0.7077        | 4.0   | 5300  | 0.7214          | 0.5170   |
| 0.7988        | 5.0   | 6625  | 0.7523          | 0.4898   |
| 0.5818        | 6.0   | 7950  | 0.8118          | 0.5510   |
| 0.7722        | 7.0   | 9275  | 0.9102          | 0.5306   |
| 1.4165        | 8.0   | 10600 | 1.6832          | 0.5      |
| 0.7113        | 9.0   | 11925 | 1.6268          | 0.5340   |
| 0.2578        | 10.0  | 13250 | 1.8423          | 0.5204   |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0