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--- |
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language: |
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- hi |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Tr - CV 43h |
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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: Common Voice 16.1 |
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type: mozilla-foundation/common_voice_16_1 |
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config: tr |
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split: None |
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args: 'config: tr, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 20.102435079521968 |
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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 Small Tr - CV 43h |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2371 |
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- Wer: 20.1024 |
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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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- gradient_accumulation_steps: 2 |
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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: 500 |
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- training_steps: 4000 |
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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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| 0.2134 | 0.37 | 500 | 0.2739 | 23.3965 | |
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| 0.1845 | 0.73 | 1000 | 0.2587 | 22.2823 | |
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| 0.1056 | 1.1 | 1500 | 0.2445 | 21.1214 | |
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| 0.1009 | 1.46 | 2000 | 0.2413 | 20.7278 | |
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| 0.0963 | 1.83 | 2500 | 0.2329 | 20.0952 | |
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| 0.0555 | 2.19 | 3000 | 0.2389 | 20.4421 | |
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| 0.0577 | 2.56 | 3500 | 0.2387 | 20.2588 | |
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| 0.0512 | 2.92 | 4000 | 0.2371 | 20.1024 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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