---
library_name: transformers
license: apache-2.0
base_model: arbml/whisper-small-ar
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: whisper-small-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: 0.5748299319727891
---

<!-- 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-small-ar-ft-kws-speech-commands

This model is a fine-tuned version of [arbml/whisper-small-ar](https://huggingface.co/arbml/whisper-small-ar) on the Speech Commands dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3471
- Accuracy: 0.5748

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- 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: 0.2
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.682         | 1.0   | 166  | 0.6867          | 0.6395   |
| 0.6463        | 2.0   | 332  | 0.6377          | 0.6531   |
| 0.5829        | 3.0   | 498  | 0.6250          | 0.6633   |
| 0.6197        | 4.0   | 664  | 0.6798          | 0.6429   |
| 0.3921        | 5.0   | 830  | 0.9584          | 0.5918   |
| 0.3009        | 6.0   | 996  | 0.9658          | 0.6395   |
| 0.123         | 7.0   | 1162 | 1.3115          | 0.6293   |
| 0.1418        | 8.0   | 1328 | 1.8621          | 0.6190   |
| 0.1181        | 9.0   | 1494 | 2.2151          | 0.6020   |
| 0.0014        | 10.0  | 1660 | 2.3968          | 0.6156   |
| 0.0007        | 11.0  | 1826 | 2.7913          | 0.5646   |
| 0.0004        | 12.0  | 1992 | 2.9198          | 0.6020   |
| 0.0003        | 13.0  | 2158 | 2.9664          | 0.5850   |
| 0.0002        | 14.0  | 2324 | 3.1507          | 0.5850   |
| 0.0002        | 15.0  | 2490 | 3.1987          | 0.5884   |
| 0.0001        | 16.0  | 2656 | 3.2650          | 0.5782   |
| 0.0001        | 17.0  | 2822 | 3.3091          | 0.5714   |
| 0.0002        | 18.0  | 2988 | 3.3048          | 0.5782   |
| 0.0023        | 19.0  | 3154 | 3.2925          | 0.5918   |
| 0.0001        | 20.0  | 3320 | 3.3471          | 0.5748   |


### Framework versions

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