metadata
language:
- el
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Greek - Robust
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 el
type: mozilla-foundation/common_voice_11_0
config: el
split: test
args: el
metrics:
- name: Wer
type: wer
value: 24.322065378900444
Whisper Medium Greek - Robust
This model is a fine-tuned version of whisper-el-medium-augmented on the mozilla-foundation/common_voice_11_0 el dataset. It achieves the following results on the evaluation set:
- Loss: 0.4312
- Wer: 24.3221
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: 5e-05
- train_batch_size: 8
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0905 | 2.35 | 1000 | 0.5419 | 37.8343 |
| 0.0552 | 4.69 | 2000 | 0.5118 | 34.6954 |
| 0.0329 | 7.04 | 3000 | 0.5332 | 32.3180 |
| 0.0219 | 9.39 | 4000 | 0.5185 | 30.1913 |
| 0.0161 | 11.74 | 5000 | 0.4908 | 32.3366 |
| 0.0063 | 14.08 | 6000 | 0.4741 | 28.4733 |
| 0.0015 | 16.43 | 7000 | 0.4400 | 26.3187 |
| 0.001 | 18.78 | 8000 | 0.4428 | 25.5293 |
| 0.0001 | 21.13 | 9000 | 0.4382 | 25.2043 |
| 0.0014 | 23.47 | 10000 | 0.4328 | 24.3221 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.7.1
- Tokenizers 0.12.1