End of training
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README.md
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name: Common Voice 17.0
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type: mozilla-foundation/common_voice_17_0
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config: id
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split:
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args: 'config: id, split: test'
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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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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.
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- Wer:
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## Model description
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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:
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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: 20
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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 Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:----:|:---------------:|:-------:|
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| 0.
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| 0.
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| 0.
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| 0.
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### Framework versions
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name: Common Voice 17.0
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type: mozilla-foundation/common_voice_17_0
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config: id
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split: train+validation+test+validated
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args: 'config: id, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 6.596506595218467
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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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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: 0.0931
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- Wer: 6.5965
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## Model description
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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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- 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 Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:----:|:---------------:|:-------:|
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| 0.2099 | 0.6002 | 1000 | 0.1998 | 14.0573 |
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| 0.0732 | 1.2005 | 2000 | 0.1336 | 9.9572 |
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| 0.0507 | 1.8007 | 3000 | 0.1034 | 7.5678 |
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| 0.0197 | 2.4010 | 4000 | 0.0931 | 6.5965 |
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### Framework versions
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