metadata
library_name: peft
language:
- hu
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 - Zakryah
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: hu
split: test
args: 'config: hu, split: test'
metrics:
- type: wer
value: 56.05556152221387
name: Wer
Whisper Medium - Zakryah
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: 0.2773
- Wer: 56.0556
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: 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 |
|---|---|---|---|---|
| 0.5683 | 0.3299 | 1000 | 0.5194 | 39.9527 |
| 0.3317 | 0.6598 | 2000 | 0.2859 | 59.6546 |
| 0.2961 | 0.9898 | 3000 | 0.2791 | 56.6892 |
| 0.2619 | 1.3197 | 4000 | 0.2773 | 56.0556 |
Framework versions
- PEFT 0.14.1.dev0
- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0