VT_Thesis_Models
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Whisper Small Frisian 10m
This model is a fine-tuned version of openai/whisper-small on the Common Voice 6.1 dataset. It achieves the following results on the evaluation set:
- Loss: 1.4198
- Wer: 56.2538
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 250
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.6208 | 3.3333 | 50 | 1.6201 | 70.3083 |
| 0.0687 | 6.6667 | 100 | 1.4034 | 58.9699 |
| 0.0038 | 10.0 | 150 | 1.3975 | 56.5104 |
| 0.0019 | 13.3333 | 200 | 1.4150 | 56.2966 |
| 0.0015 | 16.6667 | 250 | 1.4198 | 56.2538 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for xuliu15/FT-Frisian-10m_new
Base model
openai/whisper-small