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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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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-small-malayalam-colab-CV17.0 |
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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_17_0 |
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type: common_voice_17_0 |
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config: ml |
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split: test |
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args: ml |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.6534493874919407 |
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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-malayalam-colab-CV17.0 |
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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_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3197 |
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- Wer: 0.6534 |
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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: 3e-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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- 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_ratio: 0.15 |
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- training_steps: 2000 |
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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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| 0.7367 | 1.5748 | 200 | 0.2861 | 0.8443 | |
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| 0.1405 | 3.1496 | 400 | 0.2516 | 0.7550 | |
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| 0.061 | 4.7244 | 600 | 0.2315 | 0.7121 | |
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| 0.0295 | 6.2992 | 800 | 0.2600 | 0.6995 | |
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| 0.0161 | 7.8740 | 1000 | 0.2731 | 0.6721 | |
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| 0.0073 | 9.4488 | 1200 | 0.2925 | 0.6847 | |
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| 0.0033 | 11.0236 | 1400 | 0.3144 | 0.6692 | |
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| 0.0014 | 12.5984 | 1600 | 0.3111 | 0.6580 | |
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| 0.0002 | 14.1732 | 1800 | 0.3161 | 0.6557 | |
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| 0.0001 | 15.7480 | 2000 | 0.3197 | 0.6534 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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