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---
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
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