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whisper-tiny-el-lora
Fotiissss/whisper-tiny-el-lora
whisper-tiny-el-lora is a machine learning model from Fotiissss. 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
- Jun 10, 2025
- Updated
- Jun 10, 2025
- SHA
- 4a520366
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-tiny-el-lora
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7610
- Wer: 0.7897
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9613 | 5.9668 | 250 | 0.9019 | 0.8102 |
| 0.8925 | 11.9184 | 500 | 0.8434 | 0.8005 |
| 0.8578 | 17.8701 | 750 | 0.8242 | 0.8119 |
| 0.8528 | 23.8218 | 1000 | 0.8114 | 0.8133 |
| 0.8409 | 29.7734 | 1250 | 0.8012 | 0.8001 |
| 0.84 | 35.7251 | 1500 | 0.7932 | 0.8136 |
| 0.8285 | 41.6767 | 1750 | 0.7874 | 0.7946 |
| 0.8293 | 47.6284 | 2000 | 0.7822 | 0.7970 |
| 0.7985 | 53.5801 | 2250 | 0.7782 | 0.8227 |
| 0.7834 | 59.5317 | 2500 | 0.7748 | 0.8136 |
| 0.7673 | 65.4834 | 2750 | 0.7717 | 0.7994 |
| 0.7803 | 71.4350 | 3000 | 0.7692 | 0.8046 |
| 0.7774 | 77.3867 | 3250 | 0.7668 | 0.8060 |
| 0.8034 | 83.3384 | 3500 | 0.7654 | 0.8057 |
| 0.796 | 89.2900 | 3750 | 0.7641 | 0.8060 |
| 0.7909 | 95.2417 | 4000 | 0.7632 | 0.7922 |
| 0.7524 | 101.1934 | 4250 | 0.7618 | 0.7908 |
| 0.8008 | 107.1450 | 4500 | 0.7612 | 0.7901 |
| 0.8008 | 113.0967 | 4750 | 0.7610 | 0.7901 |
| 0.7678 | 119.0483 | 5000 | 0.7610 | 0.7897 |
Framework versions
- PEFT 0.15.2
- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Library
- peft
- License
- apache-2.0
- Created
- Jun 10, 2025
- Updated
- Jun 10, 2025