metadata
language:
- tr
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large V2 TR 2 - tgrhn
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 13.0
type: mozilla-foundation/common_voice_13_0
config: tr
split: None
args: 'config: tr, split: test'
metrics:
- name: Wer
type: wer
value: 13.56043956043956
Whisper Large V2 TR 2 - tgrhn
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1739
- Wer: 13.5604
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1416 | 1.0 | 5241 | 0.1766 | 16.1575 |
0.0765 | 2.0 | 10482 | 0.1639 | 14.0714 |
0.0283 | 3.0 | 15723 | 0.1739 | 13.5604 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2