Instructions to use Samuael/asr-amharic-phoneme-based-39 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Samuael/asr-amharic-phoneme-based-39 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Samuael/asr-amharic-phoneme-based-39")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Samuael/asr-amharic-phoneme-based-39") model = AutoModelForCTC.from_pretrained("Samuael/asr-amharic-phoneme-based-39") - Notebooks
- Google Colab
- Kaggle
asr-amharic-phoneme-based-39
This model was trained from scratch on the alffa_amharic dataset.
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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