metadata
library_name: transformers
language:
- ps
base_model: ihanif/whisper-small-tunning-v2
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small PS - CV20-1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
args: 'config: ps, split: test'
metrics:
- name: Wer
type: wer
value: 89.79300499643112
Whisper Small PS - CV20-1
This model is a fine-tuned version of ihanif/whisper-small-tunning-v2 on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6103
- Wer Ortho: 91.8037
- Wer: 89.7930
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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_ratio: 0.1
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 2.6485 | 1.8868 | 100 | 0.6103 | 91.8037 | 89.7930 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0