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---
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: 20.157687253613666
---
<!-- 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 - Mohammed Bakheet
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2758
- Wer: 20.1577
## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.5507 | 0.2079 | 500 | 0.3695 | 29.2247 |
| 0.2802 | 0.4158 | 1000 | 0.3148 | 26.7299 |
| 0.2408 | 0.6236 | 1500 | 0.2970 | 24.2538 |
| 0.2208 | 0.8315 | 2000 | 0.2728 | 23.3020 |
| 0.1811 | 1.0394 | 2500 | 0.2665 | 22.3935 |
| 0.1096 | 1.2473 | 3000 | 0.2641 | 21.8998 |
| 0.1068 | 1.4552 | 3500 | 0.2568 | 21.6125 |
| 0.1042 | 1.6630 | 4000 | 0.2516 | 21.0512 |
| 0.1001 | 1.8709 | 4500 | 0.2472 | 20.4092 |
| 0.0827 | 2.0788 | 5000 | 0.2469 | 20.3848 |
| 0.0672 | 2.2869 | 5500 | 0.2665 | 21.1357 |
| 0.0673 | 2.4948 | 6000 | 0.2674 | 21.5093 |
| 0.0681 | 2.7026 | 6500 | 0.2635 | 20.6101 |
| 0.0661 | 2.9105 | 7000 | 0.2602 | 20.5069 |
| 0.0494 | 3.1184 | 7500 | 0.2708 | 20.5444 |
| 0.0352 | 3.3263 | 8000 | 0.2688 | 20.5181 |
| 0.0338 | 3.5341 | 8500 | 0.2717 | 20.2515 |
| 0.0318 | 3.7420 | 9000 | 0.2723 | 20.2403 |
| 0.0309 | 3.9499 | 9500 | 0.2711 | 20.1727 |
| 0.022 | 4.1578 | 10000 | 0.2758 | 20.1577 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
|