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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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base_model: openai/whisper-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- formospeech/hat_asr_aligned |
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model-index: |
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- name: Whisper Medium Hakka Condenser |
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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 Medium Hakka Condenser |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the HAT ASR Aligned dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0401 |
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- Cer: 1.8101 |
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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: 32 |
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- eval_batch_size: 16 |
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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: 1521 |
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- training_steps: 15215 |
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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 | Cer | |
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|:-------------:|:------:|:-----:|:---------------:|:------:| |
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| 0.0328 | 0.9997 | 3043 | 0.0681 | 4.6235 | |
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| 0.0135 | 1.9993 | 6086 | 0.0515 | 2.8839 | |
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| 0.0045 | 2.9990 | 9129 | 0.0440 | 1.9904 | |
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| 0.0028 | 3.9987 | 12172 | 0.0403 | 2.0760 | |
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| 0.0007 | 4.9984 | 15215 | 0.0401 | 1.8101 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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