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whisper-large-v3-ft-malay-peft-v1
clt013/whisper-large-v3-ft-malay-peft-v1
whisper-large-v3-ft-malay-peft-v1 is a machine learning model from clt013. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. 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
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Oct 7, 2024
- Updated
- Sep 23, 2025
- SHA
- d6005c5d
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 Large v3 FT Malay - CLT013
This model is a fine-tuned version of openai/whisper-large-v3 on the Malay Speech 3k dataset. It achieves the following results on the evaluation set:
- Loss: 0.7194
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.5614 | 0.0933 | 25 | 2.6198 |
| 2.9109 | 0.1866 | 50 | 2.5967 |
| 2.5414 | 0.2799 | 75 | 2.5518 |
| 2.4919 | 0.3731 | 100 | 2.4742 |
| 2.5861 | 0.4664 | 125 | 2.3639 |
| 2.454 | 0.5597 | 150 | 2.2213 |
| 2.32 | 0.6530 | 175 | 2.0616 |
| 2.1081 | 0.7463 | 200 | 1.8668 |
| 1.7976 | 0.8396 | 225 | 1.6736 |
| 1.7597 | 0.9328 | 250 | 1.5280 |
| 1.469 | 1.0261 | 275 | 1.4172 |
| 1.4484 | 1.1194 | 300 | 1.3275 |
| 1.2641 | 1.2127 | 325 | 1.2592 |
| 1.1853 | 1.3060 | 350 | 1.1972 |
| 1.184 | 1.3993 | 375 | 1.1449 |
| 1.1733 | 1.4925 | 400 | 1.0964 |
| 1.0707 | 1.5858 | 425 | 1.0568 |
| 0.9975 | 1.6791 | 450 | 1.0172 |
| 0.9897 | 1.7724 | 475 | 0.9855 |
| 1.0223 | 1.8657 | 500 | 0.9524 |
| 0.875 | 1.9590 | 525 | 0.9232 |
| 0.9242 | 2.0522 | 550 | 0.8968 |
| 0.8829 | 2.1455 | 575 | 0.8709 |
| 0.8491 | 2.2388 | 600 | 0.8454 |
| 0.7793 | 2.3321 | 625 | 0.8236 |
| 0.7733 | 2.4254 | 650 | 0.7993 |
| 0.7085 | 2.5187 | 675 | 0.7787 |
| 0.7403 | 2.6119 | 700 | 0.7596 |
| 0.7019 | 2.7052 | 725 | 0.7415 |
| 0.722 | 2.7985 | 750 | 0.7309 |
| 0.6403 | 2.8918 | 775 | 0.7220 |
| 0.699 | 2.9851 | 800 | 0.7194 |
Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Languages
- ms
- Created
- Oct 7, 2024
- Updated
- Sep 23, 2025