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whisper-large-v3-ft-malay-peft-epoch-20
clt013/whisper-large-v3-ft-malay-peft-epoch-20
whisper-large-v3-ft-malay-peft-epoch-20 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 20, 2024
- Updated
- Sep 23, 2025
- SHA
- ef0d55b4
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: 0.4149
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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6257 | 0.3731 | 100 | 2.4258 |
| 2.3394 | 0.7463 | 200 | 1.7629 |
| 1.5256 | 1.1194 | 300 | 1.1983 |
| 1.0648 | 1.4925 | 400 | 0.9111 |
| 0.7458 | 1.8657 | 500 | 0.5754 |
| 0.5287 | 2.2388 | 600 | 0.5316 |
| 1.0221 | 2.6119 | 700 | 1.6308 |
| 0.9045 | 2.9851 | 800 | 0.4655 |
| 0.3766 | 3.3582 | 900 | 0.4186 |
| 0.3767 | 3.7313 | 1000 | 0.4082 |
| 0.355 | 4.1045 | 1100 | 0.4022 |
| 0.3284 | 4.4776 | 1200 | 0.3996 |
| 0.3229 | 4.8507 | 1300 | 0.3928 |
| 0.318 | 5.2239 | 1400 | 0.3925 |
| 0.3083 | 5.5970 | 1500 | 0.3905 |
| 0.3035 | 5.9701 | 1600 | 0.3900 |
| 0.2792 | 6.3433 | 1700 | 0.3897 |
| 0.2948 | 6.7164 | 1800 | 0.3872 |
| 0.2537 | 7.0896 | 1900 | 0.3869 |
| 0.2703 | 7.4627 | 2000 | 0.3907 |
| 0.2696 | 7.8358 | 2100 | 0.3891 |
| 0.2672 | 8.2090 | 2200 | 0.3923 |
| 0.2645 | 8.5821 | 2300 | 0.3900 |
| 0.2419 | 8.9552 | 2400 | 0.3894 |
| 0.2361 | 9.3284 | 2500 | 0.3928 |
| 0.2361 | 9.7015 | 2600 | 0.3915 |
| 0.2229 | 10.0746 | 2700 | 0.3922 |
| 0.2151 | 10.4478 | 2800 | 0.3962 |
| 0.248 | 10.8209 | 2900 | 0.3945 |
| 0.2152 | 11.1940 | 3000 | 0.3981 |
| 0.2144 | 11.5672 | 3100 | 0.4012 |
| 0.2278 | 11.9403 | 3200 | 0.3970 |
| 0.2017 | 12.3134 | 3300 | 0.4002 |
| 0.216 | 12.6866 | 3400 | 0.4018 |
| 0.2166 | 13.0597 | 3500 | 0.4013 |
| 0.2176 | 13.4328 | 3600 | 0.4043 |
| 0.2002 | 13.8060 | 3700 | 0.4054 |
| 0.1752 | 14.1791 | 3800 | 0.4066 |
| 0.1892 | 14.5522 | 3900 | 0.4048 |
| 0.2121 | 14.9254 | 4000 | 0.4078 |
| 0.209 | 15.2985 | 4100 | 0.4069 |
| 0.1857 | 15.6716 | 4200 | 0.4079 |
| 0.1867 | 16.0448 | 4300 | 0.4097 |
| 0.1833 | 16.4179 | 4400 | 0.4093 |
| 0.1918 | 16.7910 | 4500 | 0.4130 |
| 0.1815 | 17.1642 | 4600 | 0.4123 |
| 0.1854 | 17.5373 | 4700 | 0.4135 |
| 0.181 | 17.9104 | 4800 | 0.4131 |
| 0.1756 | 18.2836 | 4900 | 0.4130 |
| 0.177 | 18.6567 | 5000 | 0.4143 |
| 0.1829 | 19.0299 | 5100 | 0.4137 |
| 0.1809 | 19.4030 | 5200 | 0.4163 |
| 0.1777 | 19.7761 | 5300 | 0.4149 |
Framework versions
- PEFT 0.13.2
- 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 20, 2024
- Updated
- Sep 23, 2025