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---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- whitefox123/tashkeel
metrics:
- wer
model-index:
- name: Whisper Tiny Ar - AzeemX
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Tashkeel
type: whitefox123/tashkeel
config: default
split: None
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 40.0
---
<!-- 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 Tiny Ar - AzeemX
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Tashkeel dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2374
- Wer: 40.0
## 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2521 | 1.6 | 1000 | 0.3009 | 53.0811 |
| 0.146 | 3.2 | 2000 | 0.2476 | 42.5946 |
| 0.1238 | 4.8 | 3000 | 0.2334 | 40.1081 |
| 0.0916 | 6.4 | 4000 | 0.2372 | 39.5315 |
| 0.0866 | 8.0 | 5000 | 0.2374 | 40.0 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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