metadata
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
whisper-tiny-ar-ft-kws-speech-commands
This model is a fine-tuned version of 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