Fine-tuned using this notebook
Glaswegian_Whisper
This model is a fine-tuned version of openai/whisper-small on the Glaswegian audio dataset. It achieves the following results on the evaluation set:
- Loss: 1.4788
- Wer: 40.5394
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: 8
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0084 | 16.3934 | 1000 | 1.2802 | 38.5588 |
| 0.0019 | 32.7869 | 2000 | 1.4141 | 39.0223 |
| 0.0002 | 49.1803 | 3000 | 1.4553 | 40.3287 |
| 0.0001 | 65.5738 | 4000 | 1.4788 | 40.5394 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for divakaivan/glaswegian-asr
Base model
openai/whisper-small