metadata
language:
- az
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Azerbaijani
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 az
type: mozilla-foundation/common_voice_11_0
config: az
split: test
args: az
metrics:
- name: Wer
type: wer
value: 47.337278106508876
Whisper Medium Azerbaijani
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 az dataset. It achieves the following results on the evaluation set:
- Loss: 0.7751
- Wer: 47.3373
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
---|---|---|---|---|
0.0 | 499.0 | 1000 | 0.7751 | 47.3373 |
0.0 | 999.0 | 2000 | 0.8982 | 47.3373 |
0.0 | 1499.0 | 3000 | 0.9612 | 47.9290 |
0.0 | 1999.0 | 4000 | 1.0112 | 47.9290 |
0.0 | 2499.0 | 5000 | 1.0212 | 47.9290 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2