metadata
library_name: transformers
language:
- uz
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper medium uz - Yorkerdev
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: uz
split: test
args: 'config: uz, split: test'
metrics:
- name: Wer
type: wer
value: 30.004243528618858
Whisper medium uz - Yorkerdev
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3029
- Wer: 30.0042
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4938 | 0.2640 | 1000 | 0.4440 | 39.7007 |
| 0.3856 | 0.5280 | 2000 | 0.3592 | 33.4303 |
| 0.3381 | 0.7919 | 3000 | 0.3203 | 31.1263 |
| 0.2389 | 1.0557 | 4000 | 0.3029 | 30.0042 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.3.2
- Tokenizers 0.21.0