Whisper Medium Greek - Robust
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 el dataset. It achieves the following results on the evaluation set:
- Loss: 0.3168
- Wer: 21.6846
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: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.3865 | 1.17 | 500 | 0.5842 | 51.4487 |
0.2302 | 2.35 | 1000 | 0.4861 | 39.3202 |
0.1321 | 3.52 | 1500 | 0.4536 | 37.4257 |
0.0916 | 4.69 | 2000 | 0.4103 | 39.6824 |
0.0497 | 5.87 | 2500 | 0.4101 | 29.1883 |
0.03 | 7.04 | 3000 | 0.4121 | 28.0089 |
0.0156 | 8.22 | 3500 | 0.3842 | 26.7459 |
0.0037 | 9.39 | 4000 | 0.3433 | 28.7054 |
0.0008 | 10.56 | 4500 | 0.3244 | 21.8332 |
0.0006 | 11.74 | 5000 | 0.3178 | 21.5267 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.7.1
- Tokenizers 0.12.1
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Dataset used to train alkiskoudounas/whisper-el-medium-augmented
Space using alkiskoudounas/whisper-el-medium-augmented 1
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 eltest set self-reported21.685