metadata
library_name: transformers
language:
- ur
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small UR - Kissan Konnect
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: ur
split: validation
args: 'config: ur, split: test'
metrics:
- name: Wer
type: wer
value: 38.650605341607346
Whisper Small UR - Kissan Konnect
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8877
- Wer: 38.6506
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.2061 | 2.9806 | 1000 | 0.5796 | 37.1996 |
| 0.0302 | 5.9627 | 2000 | 0.6702 | 43.7793 |
| 0.0049 | 8.9478 | 3000 | 0.8019 | 35.7425 |
| 0.0012 | 11.9240 | 4000 | 0.8650 | 37.7654 |
| 0.0004 | 14.9001 | 5000 | 0.8877 | 38.6506 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0