|
--- |
|
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 |
|
|
