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--- |
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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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metrics: |
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- wer |
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model-index: |
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- name: vi_whisper-small |
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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: Vivos + Commonvoice |
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type: vivos |
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config: None |
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split: None |
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metrics: |
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- name: Wer |
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type: wer |
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value: 21.8855 |
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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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# vi_whisper-small |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Mixing of Vivos and CommonVoice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2894 |
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- Wer: 21.8855 |
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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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In training phase i used VIVOS dataset and cleaned CommonVoice |
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The VIVOS evaluation dataset was used |
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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: 0.0001 |
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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: 1000 |
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- training_steps: 8000 |
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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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| 0.249 | 1.1 | 1000 | 0.3766 | 32.1678 | |
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| 0.1416 | 2.2 | 2000 | 0.2881 | 46.4646 | |
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| 0.0839 | 3.3 | 3000 | 0.2799 | 22.7791 | |
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| 0.0546 | 4.41 | 4000 | 0.2894 | 21.8855 | |
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| 0.0256 | 5.51 | 5000 | 0.3023 | 32.2973 | |
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| 0.0111 | 6.61 | 6000 | 0.3061 | 31.0153 | |
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| 0.0028 | 7.71 | 7000 | 0.3143 | 27.1691 | |
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| 0.0014 | 8.81 | 8000 | 0.3187 | 27.3634 | |
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### Framework versions |
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- Transformers 4.31.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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