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whisper-medium-sr-lora
StefanJevtic63/whisper-medium-sr-lora
whisper-medium-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
- Nov 29, 2024
- Updated
- Nov 30, 2024
- SHA
- 0274c89d
Base models
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 - Serbian Model
This model is a fine-tuned version of openai/whisper-medium on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4742
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0953 | 4.6189 | 1000 | 0.3313 |
| 0.0237 | 9.2379 | 2000 | 0.3623 |
| 0.0019 | 13.8568 | 3000 | 0.4403 |
| 0.0007 | 18.4758 | 4000 | 0.4742 |
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
- Nov 29, 2024
- Updated
- Nov 30, 2024