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Model: raghadOmar/whisper-base-quran
Source: Original Platform

README.md

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+---
+language:
+- ar
+license: apache-2.0
+base_model: tarteel-ai/whisper-base-ar-quran
+tags:
+- generated_from_trainer
+datasets:
+- zolfa
+metrics:
+- wer
+model-index:
+- name: Zolfa-raghadomar
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Zolfa Dataset
+      type: zolfa
+      args: 'config: ar, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 5.263157894736842
+---
+
+<!-- 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. -->
+
+# Zolfa-raghadomar
+
+This model is a fine-tuned version of [tarteel-ai/whisper-base-ar-quran](https://huggingface.co/tarteel-ai/whisper-base-ar-quran) on the Zolfa Dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0157
+- Wer: 5.2632
+
+## 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: 5
+- training_steps: 1000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|
+| 0.0155        | 2.8571  | 100  | 0.0156          | 5.2632 |
+| 0.0037        | 5.7143  | 200  | 0.0199          | 5.2632 |
+| 0.0011        | 8.5714  | 300  | 0.0175          | 5.2632 |
+| 0.0006        | 11.4286 | 400  | 0.0123          | 5.2632 |
+| 0.0003        | 14.2857 | 500  | 0.0187          | 5.2632 |
+| 0.0001        | 17.1429 | 600  | 0.0126          | 5.2632 |
+| 0.0001        | 20.0    | 700  | 0.0159          | 5.2632 |
+| 0.0002        | 22.8571 | 800  | 0.0137          | 5.2632 |
+| 0.0001        | 25.7143 | 900  | 0.0149          | 5.2632 |
+| 0.0001        | 28.5714 | 1000 | 0.0157          | 5.2632 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1