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--- |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: whisper-medium-bem |
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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: bembaspeech |
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type: bembaspeech |
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config: bem |
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split: test |
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metrics: |
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- type: wer |
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value: 34.84 |
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name: WER |
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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: BembaSpeech |
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type: BembaSpeech |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 34.84 |
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name: WER |
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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-bem |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3519 |
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- Wer: 33.5877 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 5000 |
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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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| 0.6509 | 0.34 | 500 | 0.4872 | 50.9031 | |
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| 0.5212 | 0.67 | 1000 | 0.3972 | 40.5156 | |
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| 0.3957 | 1.01 | 1500 | 0.3451 | 36.4793 | |
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| 0.2956 | 1.34 | 2000 | 0.3421 | 37.3866 | |
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| 0.2987 | 1.68 | 2500 | 0.3206 | 34.5374 | |
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| 0.1665 | 2.02 | 3000 | 0.3290 | 34.1135 | |
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| 0.1557 | 2.35 | 3500 | 0.3334 | 35.0462 | |
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| 0.1345 | 2.69 | 4000 | 0.3374 | 33.8506 | |
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| 0.0617 | 3.02 | 4500 | 0.3445 | 33.6216 | |
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| 0.0661 | 3.36 | 5000 | 0.3519 | 33.5877 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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