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--- |
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language: |
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- zh |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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base_model: openai/whisper-small |
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datasets: |
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- mozilla-foundation/common_voice_13_0 |
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model-index: |
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- name: Whisper Small LoRA tuned zh-TW |
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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 Small LoRA tuned zh-TW |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2094 |
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- CER: 13.1583% |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 0.2284 | 1.0 | 1453 | 0.2305 | |
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| 0.2221 | 2.0 | 2906 | 0.2183 | |
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| 0.1939 | 3.0 | 4359 | 0.2149 | |
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| 0.2085 | 4.0 | 5812 | 0.2125 | |
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| 0.2202 | 5.0 | 7265 | 0.2112 | |
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| 0.2097 | 6.0 | 8718 | 0.2103 | |
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| 0.2072 | 7.0 | 10171 | 0.2095 | |
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| 0.1906 | 8.0 | 11624 | 0.2094 | |
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| 0.1818 | 9.0 | 13077 | 0.2091 | |
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| 0.2054 | 10.0 | 14530 | 0.2093 | |
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| 0.1597 | 11.0 | 15983 | 0.2094 | |
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| 0.1797 | 12.0 | 17436 | 0.2095 | |
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| 0.204 | 13.0 | 18889 | 0.2096 | |
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| 0.1872 | 14.0 | 20342 | 0.2094 | |
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| 0.1879 | 15.0 | 21795 | 0.2094 | |
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### Framework versions |
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- PEFT 0.9.1.dev0 |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
