metadata
language:
- hu
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: Whisper Large-v2 Hungarian CV11
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 hu
type: mozilla-foundation/common_voice_11_0
config: hu
split: test
args: hu
metrics:
- type: wer
value: 15.594426326712126
name: Wer
Whisper Large-v2 Hungarian CV11
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 hu dataset. It achieves the following results on the evaluation set:
- Loss: 0.3247
- Wer: 15.5944
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: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0076 | 7.52 | 1000 | 0.2607 | 16.0332 |
| 0.0013 | 15.04 | 2000 | 0.2896 | 15.7842 |
| 0.0009 | 22.55 | 3000 | 0.3042 | 16.2378 |
| 0.0003 | 30.07 | 4000 | 0.3247 | 15.5944 |
| 0.0002 | 37.59 | 5000 | 0.3313 | 15.6004 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2