Whisper Medium VI - Multi - Augmented
This model is a fine-tuned version of openai/whisper-medium on the following datasets:
It achieves the following results on the evaluation set:
- Loss: 0.3696
- Wer: 16.6594
- Cer: 7.7625
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Training:
- mozilla-foundation/common_voice_11_0 (train+validation)
- google/fleurs (train+validation)
- vivos (train)
Evaluation:
- mozilla-foundation/common_voice_11_0 (test)
- google/fleurs (test)
- vivos (test)
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
- 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 | Cer |
---|---|---|---|---|---|
0.1992 | 1.8 | 1000 | 0.2726 | 17.4929 | 8.2562 |
0.0402 | 3.6 | 2000 | 0.3317 | 17.4929 | 8.2588 |
0.0073 | 5.4 | 3000 | 0.3429 | 17.6793 | 8.8913 |
0.0014 | 7.19 | 4000 | 0.3599 | 19.0283 | 9.5103 |
0.0006 | 8.99 | 5000 | 0.3696 | 16.6594 | 7.7625 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
- Downloads last month
- 3
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Datasets used to train Scrya/whisper-medium-vi-augmented
Evaluation results
- WER on mozilla-foundation/common_voice_11_0test set self-reported16.630
- CER on mozilla-foundation/common_voice_11_0test set self-reported7.740
- WER on google/fleurstest set self-reported9.040
- CER on google/fleurstest set self-reported4.810
- WER on vivostest set self-reported8.530
- CER on vivostest set self-reported3.670