End of training

README.md

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+---
+library_name: peft
+language:
+- zh
+license: mit
+base_model: openai/whisper-large-v3-turbo
+tags:
+- wft
+- whisper
+- automatic-speech-recognition
+- audio
+- speech
+- generated_from_trainer
+datasets:
+- JacobLinCool/common_voice_19_0_zh-TW
+model-index:
+- name: whisper-large-v3-turbo-common_voice_19_0-zh-TW-full-2
+  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-large-v3-turbo-common_voice_19_0-zh-TW-full-2
+
+This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the JacobLinCool/common_voice_19_0_zh-TW dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.1939
+- eval_wer: 39.9561
+- eval_cer: 10.8721
+- eval_decode_runtime: 90.0926
+- eval_wer_runtime: 0.1222
+- eval_cer_runtime: 0.1555
+- eval_runtime: 295.1985
+- eval_samples_per_second: 16.982
+- eval_steps_per_second: 0.532
+- epoch: 0.1
+- step: 500
+
+## 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: 0.0002
+- train_batch_size: 4
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- 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: 50
+- training_steps: 5000
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.46.1
+- Pytorch 2.4.0
+- Datasets 3.0.2
+- Tokenizers 0.20.1