whisper-small / README.md
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---
language:
- ara
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- AsemBadr/GP
metrics:
- wer
model-index:
- name: Whisper Small for Quran Recognition
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Quran_Reciters
type: AsemBadr/GP
config: default
split: test
args: 'config: default, split: train'
metrics:
- name: Wer
type: wer
value: 3.747636238610968
---
<!-- 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 for Quran Recognition
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Quran_Reciters dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0193
- Wer: 3.7476
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0264 | 1.62 | 500 | 0.0319 | 8.0110 |
| 0.0012 | 3.24 | 1000 | 0.0228 | 5.5011 |
| 0.0009 | 4.85 | 1500 | 0.0209 | 4.1258 |
| 0.0003 | 6.47 | 2000 | 0.0185 | 3.7992 |
| 0.0002 | 8.09 | 2500 | 0.0188 | 3.7820 |
| 0.0001 | 9.71 | 3000 | 0.0191 | 3.7476 |
| 0.0001 | 11.33 | 3500 | 0.0193 | 3.7133 |
| 0.0 | 12.94 | 4000 | 0.0193 | 3.7476 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.1.2
- Datasets 2.17.1
- Tokenizers 0.15.1