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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-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- formospeech/tat_asr_aligned |
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model-index: |
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- name: Whisper Tiny Taiwanese 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 Tiny Taiwanese Condenser |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the TAT ASR Aligned dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6252 |
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- Cer: 11.4109 |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 32 |
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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: 681 |
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- training_steps: 6810 |
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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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| 0.3117 | 0.9985 | 681 | 0.4649 | 17.1248 | |
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| 0.1805 | 1.9971 | 1362 | 0.4360 | 13.6667 | |
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| 0.108 | 2.9956 | 2043 | 0.4497 | 13.4248 | |
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| 0.0648 | 3.9941 | 2724 | 0.4710 | 12.8500 | |
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| 0.0349 | 4.9927 | 3405 | 0.5276 | 12.7592 | |
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| 0.0192 | 5.9912 | 4086 | 0.5607 | 12.4186 | |
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| 0.0089 | 6.9897 | 4767 | 0.5911 | 12.1183 | |
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| 0.0035 | 7.9883 | 5448 | 0.6032 | 11.6608 | |
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| 0.0009 | 8.9868 | 6129 | 0.6198 | 11.5311 | |
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| 0.0005 | 9.9853 | 6810 | 0.6252 | 11.4109 | |
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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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