End of training

README.md

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+---
+library_name: transformers
+language:
+- nan
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- whisper-event
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_11_0
+metrics:
+- wer
+model-index:
+- name: Whisper Small taiwanese
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 11.0
+      type: mozilla-foundation/common_voice_11_0
+      config: nan-tw
+      split: test
+      args: nan-tw
+    metrics:
+    - name: Wer
+      type: wer
+      value: 103.93735044594301
+---
+
+<!-- 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 taiwanese
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2406
+- Wer: 103.9374
+
+## 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: 64
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 5000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer      |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 0.0007        | 39.005  | 1000 | 1.0996          | 97.8682  |
+| 0.0003        | 79.005  | 2000 | 1.1532          | 100.1958 |
+| 0.0001        | 119.005 | 3000 | 1.1976          | 102.4146 |
+| 0.0001        | 159.005 | 4000 | 1.2206          | 105.9822 |
+| 0.0001        | 199.005 | 5000 | 1.2406          | 103.9374 |
+
+
+### Framework versions
+
+- Transformers 4.50.0.dev0
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.2
+- Tokenizers 0.21.0

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