End of training
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README.md
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metrics:
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- name:
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results: []
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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-base](https://huggingface.co/openai/whisper-base) on an unknown 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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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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### Framework versions
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metrics:
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- wer
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model-index:
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- name: opus-base
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results: []
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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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# opus-base
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0177
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- Wer: 14.6250
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 24
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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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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:----:|:---------------:|:-------:|
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| 0.0281 | 0.4075 | 500 | 0.0224 | 18.3943 |
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| 0.0292 | 0.8150 | 1000 | 0.0209 | 17.6027 |
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| 0.0241 | 1.2225 | 1500 | 0.0188 | 15.7181 |
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| 0.0197 | 1.6300 | 2000 | 0.0177 | 14.6250 |
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### Framework versions
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