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shook-tiny-amharic-600hr
b1n1yam/shook-tiny-amharic-600hr
shook-tiny-amharic-600hr is a automatic speech recognition model from b1n1yam. Use it when you need speech turned into text. It is set up for transformers. 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
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Nov 18, 2025
- Updated
- Nov 21, 2025
- SHA
- 7730909b
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. -->
tiny Amharic - Biniyam Daniel
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: 0.0671
- Wer: 22.1786
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: 3e-05
- train_batch_size: 96
- eval_batch_size: 48
- seed: 42
- 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: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2949 | 0.0879 | 300 | 0.2728 | 69.7139 |
| 0.1643 | 0.1758 | 600 | 0.1619 | 48.3076 |
| 0.135 | 0.2637 | 900 | 0.1303 | 40.1983 |
| 0.1123 | 0.3516 | 1200 | 0.1142 | 35.9610 |
| 0.1011 | 0.4395 | 1500 | 0.1052 | 33.3392 |
| 0.0965 | 0.5274 | 1800 | 0.0971 | 30.9336 |
| 0.0895 | 0.6153 | 2100 | 0.0921 | 29.5138 |
| 0.0844 | 0.7032 | 2400 | 0.0867 | 28.1619 |
| 0.0803 | 0.7911 | 2700 | 0.0829 | 26.9852 |
| 0.0794 | 0.8790 | 3000 | 0.0800 | 26.1783 |
| 0.0764 | 0.9669 | 3300 | 0.0771 | 25.3417 |
| 0.0671 | 1.0548 | 3600 | 0.0752 | 24.3019 |
| 0.0712 | 1.1427 | 3900 | 0.0736 | 24.0849 |
| 0.0657 | 1.2306 | 4200 | 0.0722 | 23.6805 |
| 0.0646 | 1.3185 | 4500 | 0.0710 | 23.4355 |
| 0.0648 | 1.4064 | 4800 | 0.0699 | 23.1196 |
| 0.0627 | 1.4943 | 5100 | 0.0689 | 22.7004 |
| 0.0609 | 1.5822 | 5400 | 0.0683 | 22.5094 |
| 0.0618 | 1.6701 | 5700 | 0.0678 | 22.2923 |
| 0.0592 | 1.7580 | 6000 | 0.0675 | 22.2988 |
| 0.059 | 1.8459 | 6300 | 0.0673 | 22.1880 |
| 0.059 | 1.9338 | 6600 | 0.0671 | 22.1786 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.7.1+cu128
- Datasets 3.6.0
- Tokenizers 0.20.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- am
- Created
- Nov 18, 2025
- Updated
- Nov 21, 2025