metadata
language:
- sk
license: apache-2.0
tags:
- hf-asr-leaderboard
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Slovak
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
args: 'config: sk, split: test'
metrics:
- name: Wer
type: wer
value: 33.817229890528324
Whisper Small Slovak
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 sk dataset. It achieves the following results on the evaluation set:
- Loss: 0.6225
- Wer: 33.8172
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: 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 |
---|---|---|---|---|
0.0038 | 14.0 | 1000 | 0.5366 | 34.2575 |
0.0006 | 28.01 | 2000 | 0.5914 | 34.8881 |
0.0003 | 42.01 | 3000 | 0.6225 | 33.8172 |
0.0002 | 57.0 | 4000 | 0.6411 | 34.1385 |
0.0002 | 71.01 | 5000 | 0.6498 | 34.0195 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2