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whisper-small-nl-dy-augmentation
wangpuupup/whisper-small-nl-dy-augmentation
whisper-small-nl-dy-augmentation is a feature extraction model from wangpuupup. Use it when you need embeddings to search or compare 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
- Feature Extraction
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Jan 2, 2023
- Updated
- Jan 2, 2023
- SHA
- c17c480a
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 Small dysarthric Dutch
This model is a fine-tuned version of qmeeus/whisper-small-nl on the data/copas copas-full dataset. It achieves the following results on the evaluation set:
- Loss: 0.4702
- Wer: 22.1638
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1618 | 0.05 | 500 | 0.3787 | 28.9235 |
| 0.0583 | 1.05 | 1000 | 0.3732 | 25.7702 |
| 0.0382 | 2.05 | 1500 | 0.4001 | 25.4621 |
| 0.0316 | 3.05 | 2000 | 0.4081 | 24.7010 |
| 0.0169 | 4.05 | 2500 | 0.4325 | 24.1935 |
| 0.0153 | 5.05 | 3000 | 0.4325 | 33.4179 |
| 0.0074 | 6.05 | 3500 | 0.4367 | 23.9398 |
| 0.0096 | 7.05 | 4000 | 0.4390 | 23.3055 |
| 0.0054 | 8.05 | 4500 | 0.4441 | 23.7042 |
| 0.0032 | 9.04 | 5000 | 0.4493 | 23.2693 |
| 0.004 | 10.04 | 5500 | 0.4524 | 23.3418 |
| 0.0048 | 11.04 | 6000 | 0.4498 | 23.7224 |
| 0.001 | 12.04 | 6500 | 0.4577 | 22.8887 |
| 0.0002 | 13.04 | 7000 | 0.4577 | 22.0913 |
| 0.0001 | 14.04 | 7500 | 0.4616 | 22.1276 |
| 0.0001 | 15.04 | 8000 | 0.4639 | 22.2726 |
| 0.0001 | 16.04 | 8500 | 0.4662 | 22.1095 |
| 0.0001 | 17.04 | 9000 | 0.4684 | 22.1457 |
| 0.0001 | 18.04 | 9500 | 0.4697 | 22.1457 |
| 0.0001 | 19.04 | 10000 | 0.4702 | 22.1638 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Feature Extraction
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Jan 2, 2023
- Updated
- Jan 2, 2023