metadata
library_name: transformers
language:
- ka
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper ka
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Subtitri voice 0.1v
type: mozilla-foundation/common_voice_11_0
config: ka
split: test
args: 'config: ka, split: test'
metrics:
- name: Wer
type: wer
value: 42.44341950016089
Whisper ka
This model is a fine-tuned version of openai/whisper-small on the Subtitri voice 0.1v dataset. It achieves the following results on the evaluation set:
- Loss: 0.1584
- Wer: 42.4434
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: 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0471 | 2.9070 | 1000 | 0.0875 | 46.0260 |
| 0.0058 | 5.8140 | 2000 | 0.1194 | 44.0363 |
| 0.0004 | 8.7209 | 3000 | 0.1400 | 42.8457 |
| 0.0001 | 11.6279 | 4000 | 0.1529 | 42.5829 |
| 0.0 | 14.5349 | 5000 | 0.1584 | 42.4434 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0