End of training

README.md

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+---
+language:
+- ar
+license: apache-2.0
+base_model: openai/whisper-medium
+tags:
+- nadsoft
+- generated_from_trainer
+datasets:
+- nadsoft/arabic-98
+metrics:
+- wer
+model-index:
+- name: ./hamsa-v0.6Q
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: nadsoft/arabic-98
+      type: nadsoft/arabic-98
+    metrics:
+    - name: Wer
+      type: wer
+      value: 23.412419116812348
+---
+
+<!-- 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. -->
+
+# ./hamsa-v0.6Q
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the nadsoft/arabic-98 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2781
+- Wer: 23.4124
+
+## 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: 32
+- eval_batch_size: 16
+- 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: 300
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.9225        | 0.33  | 100  | 0.8743          | 24.5136 |
+| 0.2721        | 0.67  | 200  | 0.2782          | 24.1367 |
+| 0.2474        | 1.0   | 300  | 0.2781          | 23.4124 |
+
+
+### Framework versions
+
+- Transformers 4.37.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.2.dev0
+- Tokenizers 0.15.0