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README.md
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metrics:
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- wer
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model-index:
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- name:
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results:
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- task:
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name: Automatic Speech Recognition
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metrics:
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- name: Wer
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type: wer
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value:
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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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#
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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 11.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer:
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## Model description
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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:
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- training_steps:
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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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| 0.
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| 0.0002 | 16.26 | 4000 | 0.4603 | 545.1293 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.
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- Tokenizers 0.13.2
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metrics:
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- wer
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model-index:
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- name: whisper_marathi_test
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results:
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- task:
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name: Automatic Speech Recognition
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metrics:
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- name: Wer
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type: wer
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value: 53.72961124363355
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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_marathi_test
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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 11.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3127
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- Wer: 53.7296
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## Model description
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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: 10
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- training_steps: 300
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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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| 0.4508 | 0.41 | 100 | 0.4453 | 60.3572 |
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| 0.3239 | 0.81 | 200 | 0.3297 | 54.9159 |
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| 0.24 | 1.22 | 300 | 0.3127 | 53.7296 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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