metadata
library_name: transformers
language:
- kk
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium KK - Kazakh - Fleurs - Common Voice
results: []
datasets:
- google/fleurs
- mozilla-foundation/common_voice_17_0
Whisper Medium KK - Kazakh - Fleurs - Common Voice
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3910
- Wer: 21.2101
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: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.0045 | 7.5725 | 1000 | 0.3121 | 23.2826 |
| 0.0003 | 15.1507 | 2000 | 0.3523 | 21.3939 |
| 0.0001 | 22.7232 | 3000 | 0.3738 | 21.3661 |
| 0.0001 | 30.3013 | 4000 | 0.3863 | 21.3772 |
| 0.0001 | 37.8738 | 5000 | 0.3910 | 21.2101 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu118
- Datasets 3.6.0
- Tokenizers 0.21.0