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whisper-large-v2-sr-lora
StefanJevtic63/whisper-large-v2-sr-lora
whisper-large-v2-sr-lora is a machine learning model from StefanJevtic63. 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
- Dec 21, 2024
- Updated
- Dec 27, 2024
- SHA
- 0c66d137
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 - Serbian Model
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1118
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: 0.0009
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: linear
- lr_scheduler_warmup_steps: 400
- training_steps: 16000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2185 | 0.0705 | 500 | 0.2191 |
| 0.1764 | 0.1409 | 1000 | 0.1864 |
| 0.1752 | 0.2114 | 1500 | 0.1786 |
| 0.1703 | 0.2819 | 2000 | 0.1690 |
| 0.1558 | 0.3524 | 2500 | 0.1629 |
| 0.1584 | 0.4228 | 3000 | 0.1586 |
| 0.1496 | 0.4933 | 3500 | 0.1547 |
| 0.1592 | 0.5638 | 4000 | 0.1520 |
| 0.1428 | 0.6342 | 4500 | 0.1496 |
| 0.1429 | 0.7047 | 5000 | 0.1459 |
| 0.1357 | 0.7752 | 5500 | 0.1443 |
| 0.1332 | 0.8457 | 6000 | 0.1406 |
| 0.1413 | 0.9161 | 6500 | 0.1398 |
| 0.1373 | 0.9866 | 7000 | 0.1369 |
| 0.1253 | 1.0571 | 7500 | 0.1345 |
| 0.1229 | 1.1276 | 8000 | 0.1330 |
| 0.1114 | 1.1980 | 8500 | 0.1316 |
| 0.1189 | 1.2685 | 9000 | 0.1292 |
| 0.1116 | 1.3390 | 9500 | 0.1266 |
| 0.1108 | 1.4094 | 10000 | 0.1258 |
| 0.1098 | 1.4799 | 10500 | 0.1243 |
| 0.1112 | 1.5504 | 11000 | 0.1223 |
| 0.1139 | 1.6209 | 11500 | 0.1212 |
| 0.0951 | 1.6913 | 12000 | 0.1200 |
| 0.108 | 1.7618 | 12500 | 0.1173 |
| 0.104 | 1.8323 | 13000 | 0.1156 |
| 0.0963 | 1.9027 | 13500 | 0.1146 |
| 0.1004 | 1.9732 | 14000 | 0.1133 |
| 0.0831 | 2.0437 | 14500 | 0.1131 |
| 0.0779 | 2.1142 | 15000 | 0.1126 |
| 0.0805 | 2.1846 | 15500 | 0.1121 |
| 0.0849 | 2.2551 | 16000 | 0.1118 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.5.1
- Datasets 3.0.0
- Tokenizers 0.20.3
- Library
- peft
- License
- apache-2.0
- Languages
- sr
- Created
- Dec 21, 2024
- Updated
- Dec 27, 2024