metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small AR - Mohammed Bakheet
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ar
split: test
args: ar
metrics:
- name: Wer
type: wer
value: 20.45616669795382
Whisper Small AR - Mohammed Bakheet
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2601
- Wer: 20.4562
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-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5279 | 0.4158 | 500 | 0.3311 | 27.6591 |
| 0.2513 | 0.8316 | 1000 | 0.2866 | 24.5504 |
| 0.1673 | 1.2478 | 1500 | 0.2735 | 22.8928 |
| 0.1324 | 1.6635 | 2000 | 0.2645 | 21.8153 |
| 0.1138 | 2.0797 | 2500 | 0.2613 | 21.3816 |
| 0.064 | 2.4955 | 3000 | 0.2651 | 21.0006 |
| 0.0615 | 2.9113 | 3500 | 0.2601 | 20.4562 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3