openai/whisper-large-v2
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8091
 - Wer: 17.7875
 
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: 32
 - eval_batch_size: 16
 - seed: 42
 - distributed_type: multi-GPU
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
 - training_steps: 10000
 
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | 
|---|---|---|---|---|
| 0.2528 | 0.2 | 2000 | 0.9370 | 22.1311 | 
| 0.2718 | 0.4 | 4000 | 0.8721 | 24.9294 | 
| 0.2745 | 0.6 | 6000 | 0.8770 | 20.5292 | 
| 0.2157 | 0.8 | 8000 | 0.8774 | 18.1018 | 
| 0.1729 | 1.0 | 10000 | 0.8091 | 17.7875 | 
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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Evaluation results
- Wer on mozilla-foundation/common_voice_11_0test set self-reported38.230
 - Wer on google/fleurstest set self-reported11.600