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Mnong-ASR-v2
legendary2910/Mnong-ASR-v2
Mnong-ASR-v2 is a automatic speech recognition model from legendary2910. 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 25, 2024
- Updated
- Aug 1, 2024
- SHA
- 59b67897
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 Small Mnong
This model is a fine-tuned version of openai/whisper-small on the MnongAudio-v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3726
- Wer: 37.8757
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: 8
- 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 |
|---|---|---|---|---|
| 3.2302 | 0.2915 | 200 | 3.1116 | 239.5568 |
| 1.7352 | 0.5831 | 400 | 1.7781 | 96.5359 |
| 1.2762 | 0.8746 | 600 | 1.3745 | 100.9170 |
| 0.9605 | 1.1662 | 800 | 1.1114 | 89.1747 |
| 0.8392 | 1.4577 | 1000 | 0.9010 | 81.3551 |
| 0.6779 | 1.7493 | 1200 | 0.7770 | 64.3912 |
| 0.3956 | 2.0408 | 1400 | 0.6635 | 63.0922 |
| 0.35 | 2.3324 | 1600 | 0.6001 | 55.6037 |
| 0.3225 | 2.6239 | 1800 | 0.5402 | 59.2970 |
| 0.326 | 2.9155 | 2000 | 0.4830 | 48.0387 |
| 0.143 | 3.2070 | 2200 | 0.4697 | 41.7983 |
| 0.119 | 3.4985 | 2400 | 0.4404 | 41.5181 |
| 0.1123 | 3.7901 | 2600 | 0.4205 | 44.4727 |
| 0.0709 | 4.0816 | 2800 | 0.4009 | 38.9710 |
| 0.0764 | 4.3732 | 3000 | 0.3959 | 39.8370 |
| 0.0587 | 4.6647 | 3200 | 0.3800 | 35.8889 |
| 0.0627 | 4.9563 | 3400 | 0.3771 | 37.6465 |
| 0.0326 | 5.2478 | 3600 | 0.3754 | 35.3795 |
| 0.0355 | 5.5394 | 3800 | 0.3751 | 39.4549 |
| 0.0331 | 5.8309 | 4000 | 0.3726 | 37.8757 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- vi
- Created
- Jun 25, 2024
- Updated
- Aug 1, 2024