metadata
library_name: transformers
language:
- kn
base_model: ope100whisper-small
tags:
- generated_from_trainer
datasets:
- adithyal1998Bhat/stt_synthetic_kn-IN_kannada
metrics:
- wer
model-index:
- name: Whisper Small kn - Saraswathi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: kannada voices
type: adithyal1998Bhat/stt_synthetic_kn-IN_kannada
args: 'config: kn, split: test'
metrics:
- name: Wer
type: wer
value: 24.498620741072095
Whisper Small kn - Saraswathi
This model is a fine-tuned version of ope100whisper-small on the kannada voices dataset. It achieves the following results on the evaluation set:
- Loss: 0.1305
- Wer: 24.4986
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- 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
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1461 | 0.5869 | 1000 | 0.1511 | 37.9110 |
| 0.0795 | 1.1737 | 2000 | 0.1172 | 31.0520 |
| 0.0715 | 1.7613 | 3000 | 0.1090 | 28.1220 |
| 0.0508 | 2.3486 | 4000 | 0.1033 | 25.7362 |
| 0.0309 | 2.9356 | 5000 | 0.1101 | 25.1920 |
| 0.0474 | 3.5230 | 6000 | 0.1105 | 26.1537 |
| 0.0272 | 4.1098 | 7000 | 0.1169 | 25.4082 |
| 0.0255 | 4.6967 | 8000 | 0.1195 | 25.0727 |
| 0.0151 | 5.2835 | 9000 | 0.1285 | 24.7968 |
| 0.0149 | 5.8704 | 10000 | 0.1305 | 24.4986 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2