metadata
library_name: transformers
language:
- el
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Baseline openai/whisper-tiny on Greek. Evaluated on 1701 audio samples
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_17_0- Greek
type: mozilla-foundation/common_voice_17_0
config: el
split: None
args: 'config: el, split: test'
metrics:
- name: Wer
type: wer
value: 56.183418249189444
Baseline openai/whisper-tiny on Greek. Evaluated on 1701 audio samples
This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_17_0- Greek dataset. It achieves the following results on the evaluation set:
- Loss: 0.8397
- Wer: 56.1834
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: 64
- 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: 50
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.02 | 17.5439 | 1000 | 0.6888 | 56.2946 |
| 0.0024 | 35.0877 | 2000 | 0.8397 | 56.1834 |
| 0.001 | 52.6316 | 3000 | 0.9095 | 56.8041 |
| 0.0006 | 70.1754 | 4000 | 0.9501 | 57.0079 |
| 0.0005 | 87.7193 | 5000 | 0.9673 | 57.2487 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0