metadata
language:
- el
license: apache-2.0
tags:
- hf-asr-leaderboard
- whisper-large
- mozilla-foundation/common_voice_11_0
- greek
- whisper-event
- generated_from_trainer
- whisper-event
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
metrics:
- wer
model-index:
- name: whisper-lg-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: 9.8997
whisper-lg-el-intlv-xs
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset. It achieves the following results on the evaluation set:
- Loss: 0.2913
- Wer: 9.8997
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: 3.5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0311 | 2.49 | 1000 | 0.1809 | 10.5498 |
| 0.0074 | 4.98 | 2000 | 0.2470 | 10.2805 |
| 0.0019 | 7.46 | 3000 | 0.3008 | 10.0297 |
| 0.0011 | 9.95 | 4000 | 0.2913 | 9.8997 |
| 0.0009 | 12.44 | 5000 | 0.3092 | 10.1876 |
| 0.0005 | 14.93 | 6000 | 0.3495 | 10.1969 |
| 0.0002 | 17.41 | 7000 | 0.3659 | 10.2526 |
| 0.0001 | 19.9 | 8000 | 0.3846 | 10.2619 |
| 0.0001 | 22.39 | 9000 | 0.3941 | 10.2897 |
| 0.0001 | 24.88 | 10000 | 0.3990 | 10.3269 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2