End of training

README.md

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+---
+language:
+- ar
+license: apache-2.0
+base_model: openai/whisper-large-v3
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_16_1
+metrics:
+- wer
+model-index:
+- name: QURANIC Whisper Large V3 - revised
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common_voice_16_1
+      type: mozilla-foundation/common_voice_16_1
+      config: ar
+      split: None
+      args: 'config: ar, split: train'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 163.38589913248052
+---
+
+<!-- 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. -->
+
+# QURANIC Whisper Large V3 - revised
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common_voice_16_1 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2252
+- Wer: 163.3859
+
+## 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: 4
+- eval_batch_size: 4
+- 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: 20000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Wer      |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.3095        | 0.21  | 2000  | 0.3293          | 155.0801 |
+| 0.2412        | 0.41  | 4000  | 0.3059          | 287.9687 |
+| 0.1762        | 0.62  | 6000  | 0.2843          | 152.7845 |
+| 0.1906        | 0.82  | 8000  | 0.2645          | 124.8897 |
+| 0.0952        | 1.03  | 10000 | 0.2535          | 129.0233 |
+| 0.0955        | 1.24  | 12000 | 0.2567          | 141.4259 |
+| 0.0865        | 1.44  | 14000 | 0.2360          | 205.5690 |
+| 0.1363        | 1.65  | 16000 | 0.2288          | 187.0938 |
+| 0.1038        | 1.86  | 18000 | 0.2197          | 178.2311 |
+| 0.062         | 2.06  | 20000 | 0.2252          | 163.3859 |
+
+
+### Framework versions
+
+- Transformers 4.39.2
+- Pytorch 2.2.0
+- Datasets 2.18.0
+- Tokenizers 0.15.1

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+}

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