metadata
language:
- et
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Et - Hendrik
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: et
split: None
args: 'config: et, split: test'
metrics:
- name: Wer
type: wer
value: 72.26277372262774
Whisper Small Et - Hendrik
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.4159
- Wer: 72.2628
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2196 | 6.67 | 100 | 1.3895 | 71.5328 |
| 0.0018 | 13.33 | 200 | 1.3312 | 69.7080 |
| 0.0008 | 20.0 | 300 | 1.3874 | 71.8978 |
| 0.0006 | 26.67 | 400 | 1.4088 | 72.2628 |
| 0.0005 | 33.33 | 500 | 1.4159 | 72.2628 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2