Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Kikuyu
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use karanjaxyz/gikuyu-asr-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karanjaxyz/gikuyu-asr-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="karanjaxyz/gikuyu-asr-v0")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("karanjaxyz/gikuyu-asr-v0") model = AutoModelForSpeechSeq2Seq.from_pretrained("karanjaxyz/gikuyu-asr-v0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
gikuyu-asr-v0
This model is a fine-tuned version of openai/whisper-small on the karanjaxyz/kikuyu-asr-data dataset. It achieves the following results on the evaluation set:
- Loss: 0.2944
- Wer: 32.8628
- Cer: 10.4740
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 500
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.5621 | 0.2116 | 500 | 0.4916 | 53.2794 | 16.7317 |
| 0.4414 | 0.4232 | 1000 | 0.3852 | 42.3825 | 13.5806 |
| 0.3914 | 0.6348 | 1500 | 0.3505 | 38.0444 | 12.2589 |
| 0.3829 | 0.8464 | 2000 | 0.3302 | 36.8910 | 12.0260 |
| 0.3188 | 1.0580 | 2500 | 0.3157 | 34.6703 | 11.7171 |
| 0.3146 | 1.2696 | 3000 | 0.3089 | 34.4293 | 11.1204 |
| 0.2946 | 1.4812 | 3500 | 0.3040 | 33.9301 | 10.8692 |
| 0.3036 | 1.6928 | 4000 | 0.2974 | 33.5170 | 10.8927 |
| 0.2972 | 1.9044 | 4500 | 0.2952 | 32.8972 | 10.4897 |
| 0.2979 | 2.0 | 4726 | 0.2944 | 32.8628 | 10.4740 |
Framework versions
- Transformers 5.15.0
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2
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Model tree for karanjaxyz/gikuyu-asr-v0
Base model
openai/whisper-smallEvaluation results
- Wer on karanjaxyz/kikuyu-asr-dataself-reported32.863