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--- |
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language: |
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- ms |
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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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- clt013/malay-speech-1.6-million-rows-dataset |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium FT Malay - CLT013 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Malay Speech 1.6 million |
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type: clt013/malay-speech-1.6-million-rows-dataset |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 39.65666891696403 |
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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 FT Malay - CLT013 |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the Malay Speech 1.6 million dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7057 |
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- Wer: 39.6567 |
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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: 16 |
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- eval_batch_size: 8 |
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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: 50 |
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- training_steps: 1000 |
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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 | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 1.0434 | 0.1 | 100 | 0.9250 | 53.3417 | |
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| 0.8131 | 0.2 | 200 | 0.8394 | 46.5908 | |
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| 0.7852 | 0.3 | 300 | 0.8033 | 45.1635 | |
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| 0.7643 | 0.4 | 400 | 0.7769 | 53.5732 | |
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| 0.7424 | 0.5 | 500 | 0.7582 | 46.6969 | |
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| 0.7406 | 0.6 | 600 | 0.7451 | 39.6760 | |
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| 0.7913 | 0.7 | 700 | 0.7288 | 39.3866 | |
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| 0.7452 | 0.8 | 800 | 0.7164 | 37.9979 | |
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| 0.718 | 0.9 | 900 | 0.7099 | 38.7694 | |
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| 0.7328 | 1.0 | 1000 | 0.7057 | 39.6567 | |
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### Framework versions |
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- Transformers 4.41.2 |
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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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