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whisper-mg
nlp-mg/whisper-mg
whisper-mg is a automatic speech recognition model from nlp-mg. 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
- Jun 26, 2024
- Updated
- Jun 26, 2024
- SHA
- 15e98515
Base models
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-mg
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1375
- Wer: 7.0732
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: 16
- eval_batch_size: 1
- 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: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8228 | 35.7143 | 500 | 0.1301 | 8.2927 |
| 0.0001 | 71.4286 | 1000 | 0.1337 | 7.3171 |
| 0.0 | 107.1429 | 1500 | 0.1352 | 7.0732 |
| 0.0 | 142.8571 | 2000 | 0.1368 | 7.0732 |
| 0.0 | 178.5714 | 2500 | 0.1375 | 7.0732 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Jun 26, 2024
- Updated
- Jun 26, 2024