End of training

README.md

@@ -0,0 +1,95 @@
+---
+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: 3.163142513323019
+---
+
+<!-- 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: 0.0192
+- Wer: 3.1631
+
+## 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: 8000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.0073        | 1.62  | 500  | 0.0249          | 5.0026 |
+| 0.0014        | 3.24  | 1000 | 0.0214          | 4.1086 |
+| 0.0008        | 4.85  | 1500 | 0.0221          | 3.9883 |
+| 0.0           | 6.47  | 2000 | 0.0180          | 2.9740 |
+| 0.0           | 8.09  | 2500 | 0.0177          | 3.0944 |
+| 0.0           | 9.71  | 3000 | 0.0178          | 3.0944 |
+| 0.0           | 11.33 | 3500 | 0.0179          | 3.1288 |
+| 0.0           | 12.94 | 4000 | 0.0179          | 3.1288 |
+| 0.0           | 14.56 | 4500 | 0.0181          | 2.8881 |
+| 0.0           | 16.18 | 5000 | 0.0184          | 2.9225 |
+| 0.0           | 17.8  | 5500 | 0.0186          | 3.0256 |
+| 0.0           | 19.42 | 6000 | 0.0188          | 3.1803 |
+| 0.0           | 21.04 | 6500 | 0.0190          | 3.1631 |
+| 0.0           | 22.65 | 7000 | 0.0191          | 3.1631 |
+| 0.0           | 24.27 | 7500 | 0.0192          | 3.1803 |
+| 0.0           | 25.89 | 8000 | 0.0192          | 3.1631 |
+
+
+### Framework versions
+
+- Transformers 4.40.0.dev0
+- Pytorch 2.1.2
+- Datasets 2.17.1
+- Tokenizers 0.15.1

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+}

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