metadata
language:
- kn
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Kn - Bharat Ramanathan
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: kn_in
split: test
metrics:
- type: wer
value: 25.54
name: WER
Whisper Small Kn - Bharat Ramanathan
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1398
- Wer: 23.8167
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: 64
- eval_batch_size: 32
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4126 | 0.1 | 500 | 2.2797 | 127.2639 |
| 0.2099 | 0.1 | 1000 | 0.1774 | 28.2494 |
| 0.1736 | 0.2 | 1500 | 0.1565 | 27.5733 |
| 0.1506 | 0.3 | 2000 | 0.1514 | 26.0331 |
| 0.1373 | 0.4 | 2500 | 0.1494 | 24.4177 |
| 0.1298 | 0.5 | 3000 | 0.1456 | 25.0563 |
| 0.1198 | 1.06 | 3500 | 0.1436 | 24.4177 |
| 0.1102 | 0.1 | 4000 | 0.1452 | 24.2675 |
| 0.1097 | 0.2 | 4500 | 0.1402 | 24.3050 |
| 0.105 | 0.3 | 5000 | 0.1398 | 23.8167 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2