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whisper-large-ume-erj-v2
sage-bergerson/whisper-large-ume-erj-v2
whisper-large-ume-erj-v2 is a automatic speech recognition model from sage-bergerson. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as cc-by-nc-sa-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- cc-by-nc-sa-4.0
- Model type
- whisper
- Access
- Public
- Created
- Sep 2, 2024
- Updated
- Sep 9, 2024
- SHA
- 1544f068
Base models
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 Large UME-ERJ V2
This model is a fine-tuned version of openai/whisper-large on the UME-ERJ dataset. It achieves the following results on the evaluation set:
- Loss: 0.0568
- Wer: 0.0496
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: 5e-06
- train_batch_size: 32
- eval_batch_size: 16
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7362 | 0.1143 | 200 | 0.1780 | 0.1274 |
| 0.167 | 0.2286 | 400 | 0.1095 | 0.0852 |
| 0.1248 | 0.3429 | 600 | 0.0959 | 0.0776 |
| 0.0999 | 0.4571 | 800 | 0.0833 | 0.0669 |
| 0.0919 | 0.5714 | 1000 | 0.0821 | 0.0703 |
| 0.0839 | 0.6857 | 1200 | 0.0703 | 0.0623 |
| 0.0749 | 0.8 | 1400 | 0.0686 | 0.0611 |
| 0.0747 | 0.9143 | 1600 | 0.0689 | 0.0597 |
| 0.0624 | 1.0286 | 1800 | 0.0646 | 0.0586 |
| 0.0516 | 1.1429 | 2000 | 0.0638 | 0.0553 |
| 0.0497 | 1.2571 | 2200 | 0.0593 | 0.0521 |
| 0.0462 | 1.3714 | 2400 | 0.0634 | 0.0556 |
| 0.0454 | 1.4857 | 2600 | 0.0588 | 0.0516 |
| 0.0455 | 1.6 | 2800 | 0.0596 | 0.0540 |
| 0.0432 | 1.7143 | 3000 | 0.0622 | 0.0526 |
| 0.0401 | 1.8286 | 3200 | 0.0572 | 0.0524 |
| 0.0437 | 1.9429 | 3400 | 0.0569 | 0.0529 |
| 0.0344 | 2.0571 | 3600 | 0.0568 | 0.0496 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- cc-by-nc-sa-4.0
- Languages
- en
- Created
- Sep 2, 2024
- Updated
- Sep 9, 2024