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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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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium MS - Augmented |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: google/fleurs |
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type: google/fleurs |
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config: ms_my |
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split: test |
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args: ms_my |
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metrics: |
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- type: wer |
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value: 9.578362255965294 |
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name: WER |
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- type: cer |
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value: 2.8109053797929726 |
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name: CER |
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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 MS - Augmented |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the google/fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2066 |
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- Wer: 9.5784 |
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- Cer: 2.8109 |
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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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Training: |
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- [google/fleurs](https://huggingface.co/datasets/google/fleurs) (train+validation) |
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Evaluation: |
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- [google/fleurs](https://huggingface.co/datasets/google/fleurs) (test) |
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## Training procedure |
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Datasets were augmented on-the-fly using [audiomentations](https://github.com/iver56/audiomentations) via PitchShift and TimeStretch transformations at `p=0.3`. |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 32 |
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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: 100 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:| |
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| 0.0876 | 2.15 | 200 | 0.1949 | 10.3105 | 3.0685 | |
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| 0.0064 | 4.3 | 400 | 0.1974 | 9.7004 | 2.9596 | |
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| 0.0014 | 6.45 | 600 | 0.2031 | 9.6190 | 2.8955 | |
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| 0.001 | 8.6 | 800 | 0.2058 | 9.6055 | 2.8440 | |
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| 0.0009 | 10.75 | 1000 | 0.2066 | 9.5784 | 2.8109 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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