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
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Datasets used to train farsipal/whisper-lg-el-intlv-xs
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0test set self-reported9.900