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whisper-dpv-finetuned-WITH-PUNCTUATION
aherzberg/whisper-dpv-finetuned-WITH-PUNCTUATION
whisper-dpv-finetuned-WITH-PUNCTUATION is a automatic speech recognition model from aherzberg. 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
- Dec 20, 2022
- Updated
- Dec 20, 2022
- SHA
- 6df7d8e4
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-dpv-finetuned-WITH-PUNCTUATION
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6549
- Wer: 35.3154
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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3015 | 1.25 | 1000 | 0.5604 | 37.1241 |
| 0.1215 | 2.49 | 2000 | 0.5759 | 35.5189 |
| 0.0338 | 3.74 | 3000 | 0.6549 | 35.3154 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Dec 20, 2022
- Updated
- Dec 20, 2022