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whisper-SER-base-v2
iFaz/whisper-SER-base-v2
whisper-SER-base-v2 is a automatic speech recognition model from iFaz. 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 17, 2025
- Updated
- Jan 17, 2025
- SHA
- 5ea36974
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-SER-base-v2
This model is a fine-tuned version of openai/whisper-base on the facebook_voxpopulik_16k_Whisper_Compatible dataset. It achieves the following results on the evaluation set:
- Loss: 0.5113
- Wer: 31.9908
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: 4
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 12000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4753 | 0.4322 | 1000 | 0.4532 | 24.8077 |
| 0.4303 | 0.8643 | 2000 | 0.4212 | 25.1645 |
| 0.2697 | 1.2965 | 3000 | 0.4265 | 27.7174 |
| 0.2267 | 1.7286 | 4000 | 0.4122 | 27.1307 |
| 0.1764 | 2.1608 | 5000 | 0.4505 | 39.1422 |
| 0.2175 | 2.5929 | 6000 | 0.4206 | 26.8770 |
| 0.0845 | 3.0251 | 7000 | 0.4547 | 32.9739 |
| 0.0907 | 3.4572 | 8000 | 0.4707 | 28.8353 |
| 0.0968 | 3.8894 | 9000 | 0.4768 | 32.9660 |
| 0.0495 | 4.3215 | 10000 | 0.5026 | 31.2455 |
| 0.051 | 4.7537 | 11000 | 0.5037 | 32.8312 |
| 0.0668 | 5.1858 | 12000 | 0.5113 | 31.9908 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- en
- Created
- Jan 17, 2025
- Updated
- Jan 17, 2025