metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: kyrgyz_asr
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: ky
split: None
args: ky
metrics:
- name: Wer
type: wer
value: 38.50746268656716
kyrgyz_asr
This model is a fine-tuned version of openai/whisper-tiny on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3324
- Wer: 38.5075
Model description
This is a test fine-tuning of Whisper Tiny for the Kyrgyz language using a dataset from the Mozilla Foundation. The code is taken from this source.
Intended uses & limitations
More information needed
Training and evaluation data
mozilla-foundation/common_voice_17_0 (ky - kyrgyz)
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.59 | 0.4735 | 1000 | 0.5917 | 60.8051 |
| 0.4987 | 0.9470 | 2000 | 0.4195 | 47.8517 |
| 0.3932 | 1.4205 | 3000 | 0.3561 | 42.6685 |
| 0.3441 | 1.8939 | 4000 | 0.3324 | 38.5075 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0