Whisper Medium Ro - Sarbu Vlad - multi gpu
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 16.1 + Romanian speech synthesis dataset. It achieves the following results on the evaluation set:
- Loss: 0.1620
- Wer: 12.1820
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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 48
- total_eval_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.148 | 0.98 | 250 | 0.1494 | 14.1574 |
| 0.0875 | 1.96 | 500 | 0.1295 | 12.9080 |
| 0.0404 | 2.94 | 750 | 0.1285 | 11.8734 |
| 0.0227 | 3.92 | 1000 | 0.1353 | 12.1094 |
| 0.0139 | 4.9 | 1250 | 0.1409 | 11.9702 |
| 0.0076 | 5.88 | 1500 | 0.1539 | 12.0459 |
| 0.005 | 6.86 | 1750 | 0.1599 | 12.1880 |
| 0.0039 | 7.84 | 2000 | 0.1620 | 12.1820 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.1
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Model tree for VladS159/Whisper_medium_ro_VladS_2000_steps_multi_gpu_23_02_2024
Base model
openai/whisper-mediumDataset used to train VladS159/Whisper_medium_ro_VladS_2000_steps_multi_gpu_23_02_2024
Evaluation results
- Wer on Common Voice 16.1 + Romanian speech synthesisself-reported12.182