Whisper Small fine tune-Edmund-0818
This model is a fine-tuned version of openai/whisper-small on the Preach_speech_finetuning dataset. It achieves the following results on the evaluation set:
- Loss: 0.1966
- Wer: 30.4762
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: 1.25e-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_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
No log | 1.0 | 156 | 0.1196 | 17.1429 |
No log | 2.0 | 312 | 0.1553 | 24.6032 |
No log | 3.0 | 468 | 0.1655 | 26.5079 |
0.0806 | 4.0 | 624 | 0.1820 | 29.5238 |
0.0806 | 5.0 | 780 | 0.1792 | 30.1587 |
0.0806 | 6.0 | 936 | 0.1998 | 31.5873 |
0.0131 | 7.0 | 1092 | 0.1954 | 31.2698 |
0.0131 | 8.0 | 1248 | 0.1923 | 30.6349 |
0.0131 | 9.0 | 1404 | 0.1905 | 31.2698 |
0.0016 | 10.0 | 1560 | 0.1954 | 31.2698 |
0.0016 | 11.0 | 1716 | 0.1931 | 31.1111 |
0.0016 | 12.0 | 1872 | 0.1953 | 30.4762 |
0.0005 | 13.0 | 2028 | 0.1960 | 30.6349 |
0.0005 | 14.0 | 2184 | 0.1964 | 30.6349 |
0.0005 | 15.0 | 2340 | 0.1966 | 30.4762 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for edmundchan70/Cantonese_Whisper_finetune
Base model
openai/whisper-small