metadata
language:
- ks
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- muneebharoon/whisper-kashmiri
metrics:
- wer
model-index:
- name: Whisper Medium ks - Muneeb Haroon
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: whisper-kashmiri
type: muneebharoon/whisper-kashmiri
args: 'config: ks, split: test'
metrics:
- name: Wer
type: wer
value: 42.32558139534884
Whisper Medium ks - Muneeb Haroon
This model is a fine-tuned version of openai/whisper-medium on the whisper-kashmiri dataset. It achieves the following results on the evaluation set:
- Loss: 1.2108
- Wer: 42.3256
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: 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0024 | 71.43 | 1000 | 1.0586 | 44.0930 |
| 0.0002 | 142.86 | 2000 | 1.2108 | 42.3256 |
| 0.0001 | 214.29 | 3000 | 1.3416 | 42.5581 |
| 0.0 | 285.71 | 4000 | 1.4482 | 42.9302 |
| 0.0 | 357.14 | 5000 | 1.5533 | 42.9302 |
| 0.0 | 428.57 | 6000 | 1.6342 | 43.4884 |
| 0.0 | 500.0 | 7000 | 1.7142 | 43.1628 |
| 0.0 | 571.43 | 8000 | 1.7657 | 43.4419 |
| 0.0 | 642.86 | 9000 | 1.8178 | 43.5349 |
| 0.0 | 714.29 | 10000 | 1.8312 | 43.6744 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2