metadata
language:
- el
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
- hf-asr-leaderboard
- automatic-speech-recognition
- greek
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
metrics:
- wer
model-index:
- name: whisper-sm-el-intlv-xs
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
config: el
split: test
metrics:
- name: Wer
type: wer
value: 20.068722139673106
Whisper small (Greek) Trained on Interleaved Datasets
This model is a fine-tuned version of openai/whisper-small on interleaved mozilla-foundation/common_voice_11_0 (el) and google/fleurs (el_gr) dataset. It achieves the following results on the evaluation set:
- Loss: 0.4741
- Wer: 20.0687
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.0186 | 4.98 | 1000 | 0.3619 | 21.0067 |
| 0.0012 | 9.95 | 2000 | 0.4347 | 20.3009 |
| 0.0005 | 14.93 | 3000 | 0.4741 | 20.0687 |
| 0.0003 | 19.9 | 4000 | 0.4974 | 20.1152 |
| 0.0003 | 24.88 | 5000 | 0.5066 | 20.2266 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.12.1