metadata
language:
- de
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- rmacek/common_voice_zib2
metrics:
- wer
model-index:
- name: Whisper Small ZIB2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ZIB2 Common Voice
type: rmacek/common_voice_zib2
args: 'config: de, split: test'
metrics:
- name: Wer
type: wer
value: 28.93835616438356
Whisper Small ZIB2
This model is a fine-tuned version of openai/whisper-small on the ZIB2 Common Voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.3366
- Wer: 28.9384
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2391 | 10.0 | 100 | 0.2837 | 33.5616 |
| 0.0035 | 20.0 | 200 | 0.2701 | 27.7397 |
| 0.0012 | 30.0 | 300 | 0.2847 | 27.5685 |
| 0.0006 | 40.0 | 400 | 0.2990 | 27.9110 |
| 0.0004 | 50.0 | 500 | 0.3118 | 28.5959 |
| 0.0003 | 60.0 | 600 | 0.3221 | 28.5959 |
| 0.0002 | 70.0 | 700 | 0.3287 | 28.7671 |
| 0.0002 | 80.0 | 800 | 0.3333 | 28.9384 |
| 0.0002 | 90.0 | 900 | 0.3357 | 28.9384 |
| 0.0002 | 100.0 | 1000 | 0.3366 | 28.9384 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2