Downloads · 30 days
12
40% of all-time downloads
whisper-large-v2-ru-tuned
mzzae/whisper-large-v2-ru-tuned
whisper-large-v2-ru-tuned is a automatic speech recognition model from mzzae. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
30
Public
Parameters
1.5B
12.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors6.2 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- whisper
- Access
- Public
- Created
- Feb 24, 2025
- Updated
- Feb 25, 2025
- SHA
- fd4c983c
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-v2-ru-tuned
This model was trained from scratch on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1714
- Wer Ortho: 13.2854
- Wer: 9.7737
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 12000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho |
|---|---|---|---|---|---|
| 0.0806 | 0.1231 | 500 | 0.1944 | 10.7828 | 15.1977 |
| 0.1386 | 0.2462 | 1000 | 0.1729 | 9.8746 | 13.9468 |
| 0.1309 | 0.3693 | 1500 | 0.1624 | 10.0187 | 14.2056 |
| 0.1101 | 0.4924 | 2000 | 0.1543 | 9.7160 | 13.4292 |
| 0.1589 | 0.6155 | 2500 | 0.1571 | 9.6007 | 13.4148 |
| 0.1479 | 0.7386 | 3000 | 0.1553 | 13.6017 | 9.9611 |
| 0.1133 | 0.8616 | 3500 | 0.1535 | 12.6671 | 9.4133 |
| 0.1472 | 0.9847 | 4000 | 0.1472 | 12.3940 | 9.0529 |
| 0.0584 | 1.1078 | 4500 | 0.1567 | 12.9260 | 9.2547 |
| 0.064 | 1.2309 | 5000 | 0.1569 | 13.7168 | 9.9178 |
| 0.0657 | 1.3540 | 5500 | 0.1713 | 14.0187 | 10.4368 |
| 0.0712 | 1.4771 | 6000 | 0.1664 | 14.4069 | 10.7539 |
| 0.0793 | 1.6002 | 6500 | 0.1607 | 12.7678 | 9.1106 |
| 0.068 | 1.7233 | 7000 | 0.1637 | 12.3364 | 8.8078 |
| 0.0646 | 1.8464 | 7500 | 0.1623 | 13.0122 | 9.5286 |
| 0.0747 | 1.9695 | 8000 | 0.1580 | 12.3652 | 9.2691 |
| 0.0346 | 2.0926 | 8500 | 0.1674 | 12.7534 | 9.4133 |
| 0.04 | 2.2157 | 9000 | 0.1725 | 13.2135 | 9.1826 |
| 0.0346 | 2.3387 | 9500 | 0.1710 | 12.6096 | 8.8655 |
| 0.0418 | 2.4618 | 10000 | 0.1771 | 14.6226 | 10.8837 |
| 0.0482 | 2.5849 | 10500 | 0.1688 | 13.2135 | 9.5863 |
| 0.0464 | 2.7080 | 11000 | 0.1774 | 13.6592 | 9.9899 |
| 0.0358 | 2.8311 | 11500 | 0.1731 | 13.0841 | 9.4710 |
| 0.044 | 2.9542 | 12000 | 0.1714 | 13.2854 | 9.7737 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- Created
- Feb 24, 2025
- Updated
- Feb 25, 2025