metadata
library_name: transformers
language:
- lo
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 Lo - TopSlayer
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: hi, split: test'
metrics:
- name: Wer
type: wer
value: 27.397260273972602
Whisper Small Lo - TopSlayer
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: 0.4486
- Wer: 27.3973
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: 5
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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 |
|---|---|---|---|---|
| 0.0071 | 20.8333 | 1000 | 0.3643 | 43.8356 |
| 0.0013 | 41.6667 | 2000 | 0.3832 | 36.9863 |
| 0.0 | 62.5 | 3000 | 0.4228 | 27.3973 |
| 0.0 | 83.3333 | 4000 | 0.4416 | 27.3973 |
| 0.0 | 104.1667 | 5000 | 0.4486 | 27.3973 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0