Finetune Whisper on Frisian and English
Collection
Assessing Knowledge-Distillation Based Compression of Whisper Model for Frisian ASR
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12 items
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Updated
DistilFT-Frisian-10m
This model is a fine-tuned version of distil-small.en on the mozilla-foundation/common_voice_6_fy_NL dataset. It achieves the following results on the evaluation set:
- Loss: 4.1946
- Wer: 89.3637
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: 0.0001
- 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: 200
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1154 | 33.3333 | 500 | 3.7440 | 105.5534 |
| 0.0107 | 66.6667 | 1000 | 4.0814 | 88.1911 |
| 0.0 | 100.0 | 1500 | 4.1314 | 90.7432 |
| 0.0 | 133.3333 | 2000 | 4.1700 | 89.8663 |
| 0.0 | 166.6667 | 2500 | 4.1878 | 89.6061 |
| 0.0 | 200.0 | 3000 | 4.1946 | 89.3637 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Dataset used to train Pageee/DistilFT-Frisian-10md
Collection including Pageee/DistilFT-Frisian-10md
Evaluation results
- Wer on mozilla-foundation/common_voice_6_fy_NLself-reported89.364