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--- |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- kul-speech-lab/CGN |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium CGN |
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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: kul-speech-lab/CGN |
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type: kul-speech-lab/CGN |
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config: cgn-dev.py |
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split: test |
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metrics: |
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- name: Wer |
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type: wer |
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value: 10.727751271110364 |
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--- |
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# Whisper Medium CGN |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the kul-speech-lab/CGN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2639 |
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- Wer: 10.7278 |
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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: 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: 500 |
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- training_steps: 15000 |
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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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| 0.1116 | 1.01 | 1000 | 0.2978 | 15.2127 | |
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| 0.0786 | 2.03 | 2000 | 0.2842 | 13.4852 | |
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| 0.2042 | 3.04 | 3000 | 0.2656 | 13.3590 | |
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| 0.1183 | 4.05 | 4000 | 0.2667 | 12.6977 | |
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| 0.0584 | 6.01 | 5000 | 0.2604 | 12.0993 | |
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| 0.0126 | 7.02 | 6000 | 0.2776 | 12.1477 | |
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| 0.0837 | 8.04 | 7000 | 0.2541 | 11.9397 | |
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| 0.0229 | 9.05 | 8000 | 0.2663 | 11.3221 | |
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| 0.042 | 11.01 | 9000 | 0.2549 | 11.4863 | |
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| 0.0075 | 12.02 | 10000 | 0.2775 | 11.0780 | |
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| 0.008 | 13.03 | 11000 | 0.2499 | 10.9759 | |
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| 0.0739 | 14.05 | 12000 | 0.2308 | 10.9441 | |
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| 0.0379 | 16.01 | 13000 | 0.2423 | 10.7926 | |
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| 0.02 | 17.02 | 14000 | 0.2629 | 10.7699 | |
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| 0.0111 | 18.03 | 15000 | 0.2639 | 10.7278 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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Whisper medium model finetuned on Flemish part of Corpus Gesproken Nederlands (CGN). |
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