metadata
language:
- et
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: 'Whisper Small et '
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: test
args: et
metrics:
- name: Wer
type: wer
value: 45.727838353970306
Whisper Small et
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: 0.9972
- Wer: 45.7278
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: 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 |
|---|---|---|---|---|
| 0.0045 | 19.01 | 1000 | 0.8365 | 46.1129 |
| 0.0031 | 39.01 | 2000 | 0.9022 | 46.4116 |
| 0.0005 | 59.01 | 3000 | 0.9536 | 45.3921 |
| 0.0003 | 79.01 | 4000 | 0.9844 | 45.7771 |
| 0.0003 | 99.01 | 5000 | 0.9972 | 45.7278 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2