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whisper-medium-1hr
mn367/whisper-medium-1hr
whisper-medium-1hr is a automatic speech recognition model from mn367. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Jan 2, 2023
- Updated
- Jan 2, 2023
- SHA
- e35e07fd
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
Whisper Medium 1hr
This model is a fine-tuned version of openai/whisper-medium on the Radio dataset dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.6053
- eval_wer: 17.5426
- eval_runtime: 651.6941
- eval_samples_per_second: 2.363
- eval_steps_per_second: 0.296
- epoch: 37.5
- step: 900
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1600
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- en
- Created
- Jan 2, 2023
- Updated
- Jan 2, 2023