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Whisper Small Ro - PEFT
This model is a fine-tuned version of openai/whisper-small on the Romanian Speech Dataset + 5% Synthetic dataset. It achieves the following results on the evaluation set:
- Loss: 0.4248
- Wer: 106.5981
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.0921 | 0.0113 | 50 | 1.0811 | 95.9014 |
| 0.6328 | 0.0227 | 100 | 0.4248 | 106.5981 |
Framework versions
- PEFT 0.18.1.dev0
- Transformers 4.57.1
- Pytorch 2.9.1+rocm6.4
- Datasets 3.6.0
- Tokenizers 0.22.1
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Model tree for VladS159/test2
Base model
openai/whisper-smallDataset used to train VladS159/test2
Evaluation results
- Wer on Romanian Speech Dataset + 5% Syntheticself-reported106.598
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("VladS159/test2", dtype="auto")