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Model: Bagus/whisper-medium-common_voice_17_0-id-10000 Source: Original Platform
2026-05-16 02:52:47 +08:00
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+---
+license: apache-2.0
+base_model: openai/whisper-medium
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_17_0
+metrics:
+- wer
+model-index:
+- name: whisper-medium-common_voice_17_0-id-10000
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: mozilla-foundation/common_voice_17_0 id
+      type: mozilla-foundation/common_voice_17_0
+      config: id
+      split: None
+      args: id
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.04241496125110214
+---
+
+<!-- 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-medium-common_voice_17_0-id-10000
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_17_0 id dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0574
+- Wer: 0.0424
+
+## 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: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 10000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
+|:-------------:|:------:|:-----:|:---------------:|:------:|
+| 0.132         | 0.8457 | 1000  | 0.0963          | 0.0747 |
+| 0.0503        | 1.6913 | 2000  | 0.0664          | 0.0526 |
+| 0.023         | 2.5370 | 3000  | 0.0628          | 0.0727 |
+| 0.011         | 3.3827 | 4000  | 0.0593          | 0.0437 |
+| 0.0033        | 4.2283 | 5000  | 0.0575          | 0.0407 |
+| 0.0017        | 5.0740 | 6000  | 0.0574          | 0.0448 |
+| 0.0013        | 5.9197 | 7000  | 0.0554          | 0.0386 |
+| 0.002         | 6.7653 | 8000  | 0.0555          | 0.0426 |
+| 0.0002        | 7.6110 | 9000  | 0.0571          | 0.0421 |
+| 0.0005        | 8.4567 | 10000 | 0.0574          | 0.0424 |
+
+
+### Framework versions
+
+- Transformers 4.42.0.dev0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1