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--- |
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library_name: peft |
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language: |
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- zh |
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license: apache-2.0 |
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base_model: openai/whisper-large-v2 |
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tags: |
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- wft |
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- whisper |
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- automatic-speech-recognition |
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- audio |
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- speech |
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- generated_from_trainer |
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datasets: |
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- JacobLinCool/common_voice_19_0_zh-TW |
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model-index: |
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- name: whisper-large-v2-common_voice_19_0-zh-TW-full-1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# whisper-large-v2-common_voice_19_0-zh-TW-full-1 |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co./openai/whisper-large-v2) on the JacobLinCool/common_voice_19_0_zh-TW dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.1192 |
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- eval_wer: 42.0108 |
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- eval_cer: 17.1669 |
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- eval_decode_runtime: 91.7088 |
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- eval_wer_runtime: 0.1238 |
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- eval_cer_runtime: 0.1555 |
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- eval_runtime: 334.8833 |
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- eval_samples_per_second: 14.969 |
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- eval_steps_per_second: 0.469 |
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- epoch: 0.3 |
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- step: 1500 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 4 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 5000 |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
