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---
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language:
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- en
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license: apache-2.0
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tags:
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- en-asr-leaderboard
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- generated_from_trainer
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datasets:
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- mn367/radio-test-dataset
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model-index:
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- name: Whisper Medium 2hr
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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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# Whisper Medium 2hr
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Radio dataset dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.4054
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- eval_wer: 15.0273
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- eval_runtime: 415.198
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- eval_samples_per_second: 2.317
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- eval_steps_per_second: 0.291
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- epoch: 13.11
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- step: 800
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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: 1e-06
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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_steps: 1600
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu116
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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