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whisper-el-medium-augmented
ALM/whisper-el-medium-augmented
whisper-el-medium-augmented is a automatic speech recognition model from ALM. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Dec 19, 2022
- Updated
- Dec 22, 2022
- SHA
- 2fdc19ef
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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: 0.2807
- Wer: 17.7099
IMPORTANT The model has been trained using data augmentation to improve its generalization capabilities and robustness. The results on the eval set during training are biased towards data augmentation applied to evaluation data.
Results on eval set
- Mozilla CV 11.0 - Greek: 13.250 WER (using official script)
- Google Fluers - Greek: 39.59 WER (using official script)
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: 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: 20000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0407 | 4.69 | 2000 | 0.2484 | 20.8767 |
| 0.0128 | 9.39 | 4000 | 0.2795 | 21.2017 |
| 0.0041 | 14.08 | 6000 | 0.2744 | 19.1308 |
| 0.0017 | 18.78 | 8000 | 0.2759 | 17.9978 |
| 0.0005 | 23.47 | 10000 | 0.2751 | 18.5457 |
| 0.0015 | 28.17 | 12000 | 0.2928 | 19.2051 |
| 0.0004 | 32.86 | 14000 | 0.2819 | 18.2857 |
| 0.0002 | 37.56 | 16000 | 0.2831 | 17.7285 |
| 0.0007 | 42.25 | 18000 | 0.2776 | 17.8399 |
| 0.0 | 46.95 | 20000 | 0.2792 | 17.0970 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.7.1
- Tokenizers 0.12.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- el
- Created
- Dec 19, 2022
- Updated
- Dec 22, 2022