Training finished

README.md

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+---
+library_name: transformers
+language:
+- ar
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Whisper tiny AR - BH
+  results: []
+---
+
+<!-- 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 - BH
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the quran-ayat-speech-to-text dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0103
+- Wer: 10.6202
+- Cer: 3.3954
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Cer     | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:-------:|:---------------:|:-------:|
+| 0.0292        | 0.0704 | 200  | 10.4216 | 0.0261          | 33.1910 |
+| 0.0197        | 0.1408 | 400  | 8.7672  | 0.0199          | 25.3217 |
+| 0.0169        | 0.2112 | 600  | 8.0395  | 0.0169          | 22.2440 |
+| 0.0144        | 0.2817 | 800  | 6.0399  | 0.0161          | 18.5408 |
+| 0.011         | 0.3521 | 1000 | 5.5138  | 0.0148          | 17.3477 |
+| 0.0092        | 0.4225 | 1200 | 5.0008  | 0.0136          | 16.7994 |
+| 0.0087        | 0.4929 | 1400 | 4.7966  | 0.0134          | 14.8045 |
+| 0.0078        | 0.5633 | 1600 | 4.5948  | 0.0128          | 14.1680 |
+| 0.0056        | 0.6337 | 1800 | 4.7204  | 0.0112          | 13.6886 |
+| 0.0059        | 0.7042 | 2000 | 4.2984  | 0.0117          | 13.2643 |
+| 0.0052        | 0.7746 | 2200 | 4.0641  | 0.0111          | 12.5892 |
+| 0.0041        | 0.8450 | 2400 | 3.8254  | 0.0109          | 11.9527 |
+| 0.0043        | 0.9154 | 2600 | 0.0105  | 11.8177         | 3.8392  |
+| 0.004         | 0.9858 | 2800 | 0.0105  | 11.7406         | 3.7978  |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

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+}

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