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shook-medium-amharic-2k
b1n1yam/shook-medium-amharic-2k
shook-medium-amharic-2k is a automatic speech recognition model from b1n1yam. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- whisper
- Access
- Public
- Created
- Dec 8, 2025
- Updated
- Dec 12, 2025
- SHA
- 60b7ae17
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. -->
shook-medium-amharic-2k
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0532
- Wer: 9.1091
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.1306 | 0.0741 | 1000 | 0.1286 | 35.3980 |
| 0.0923 | 0.1482 | 2000 | 0.0923 | 26.9373 |
| 0.0742 | 0.2224 | 3000 | 0.0797 | 23.8271 |
| 0.0727 | 0.2965 | 4000 | 0.0748 | 23.6953 |
| 0.0706 | 0.3706 | 5000 | 0.0708 | 22.7201 |
| 0.0614 | 0.4447 | 6000 | 0.0689 | 22.0611 |
| 0.065 | 0.5189 | 7000 | 0.0671 | 21.5340 |
| 0.0594 | 0.5930 | 8000 | 0.0640 | 21.1650 |
| 0.0563 | 0.6671 | 9000 | 0.0619 | 21.1386 |
| 0.06 | 0.7412 | 10000 | 0.0618 | 21.1650 |
| 0.055 | 0.8153 | 11000 | 0.0597 | 20.6378 |
| 0.0558 | 0.8895 | 12000 | 0.0595 | 20.6115 |
| 0.0513 | 0.9636 | 13000 | 0.0584 | 19.8208 |
| 0.0521 | 1.0377 | 14000 | 0.0567 | 20.2161 |
| 0.0482 | 1.1118 | 15000 | 0.0567 | 20.0316 |
| 0.0458 | 1.1859 | 16000 | 0.0563 | 17.9789 |
| 0.0487 | 1.2600 | 17000 | 0.0559 | 14.7153 |
| 0.0448 | 1.3341 | 18000 | 0.0554 | 14.7417 |
| 0.0411 | 1.4083 | 19000 | 0.0553 | 13.4254 |
| 0.0407 | 1.4824 | 20000 | 0.0542 | 11.2145 |
| 0.0455 | 1.5565 | 21000 | 0.0539 | 11.1355 |
| 0.0439 | 1.6306 | 22000 | 0.0537 | 11.8719 |
| 0.0427 | 1.7048 | 23000 | 0.0538 | 11.2936 |
| 0.0389 | 1.7789 | 24000 | 0.0534 | 9.9773 |
| 0.0385 | 1.8530 | 25000 | 0.0533 | 9.0828 |
| 0.0366 | 1.9271 | 26000 | 0.0532 | 9.1091 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.7.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- Created
- Dec 8, 2025
- Updated
- Dec 12, 2025