metadata
language:
- ne
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- openslr/slr43
metrics:
- wer
model-index:
- name: Whisper small nepali - Rikesh Silwal
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: slr43
type: openslr/slr43
args: 'config: ne, split: test'
metrics:
- name: Wer
type: wer
value: 33.719892952720784
Whisper small nepali - Rikesh Silwal
This model is a fine-tuned version of openai/whisper-small on the slr43 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3583
- Wer: 33.7199
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0061 | 9.62 | 1000 | 0.3096 | 36.4853 |
| 0.0001 | 19.23 | 2000 | 0.3306 | 34.2551 |
| 0.0 | 28.85 | 3000 | 0.3525 | 33.5712 |
| 0.0 | 38.46 | 4000 | 0.3583 | 33.7199 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2