lab9_whisper-tiny-zh-tw
This model is a fine-tuned version of Wellyowo/whisper-tiny-zh-tw on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6336
- Wer Ortho: 64.0
- Wer: 62.1359
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
0.0088 | 0.6882 | 500 | 0.5502 | 60.0 | 61.1650 |
0.0051 | 1.3765 | 1000 | 0.5735 | 65.0 | 64.0777 |
0.0068 | 2.0647 | 1500 | 0.5820 | 63.0 | 63.1068 |
0.0021 | 2.7529 | 2000 | 0.5955 | 62.0 | 61.1650 |
0.0039 | 3.4412 | 2500 | 0.5858 | 62.0 | 61.1650 |
0.0018 | 4.1294 | 3000 | 0.5981 | 63.0 | 61.1650 |
0.0019 | 4.8176 | 3500 | 0.6322 | 63.0 | 61.1650 |
0.0102 | 5.5058 | 4000 | 0.6336 | 64.0 | 62.1359 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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