whisper-tiny-khmer-aug-v5
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2692
- Wer: 65.8991
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.8233 | 1.0 | 793 | 0.4089 | 85.6008 |
0.3463 | 2.0 | 1586 | 0.2983 | 79.4389 |
0.2618 | 3.0 | 2379 | 0.2675 | 83.5739 |
0.2207 | 4.0 | 3172 | 0.2512 | 76.1635 |
0.1929 | 5.0 | 3965 | 0.2446 | 69.3692 |
0.1709 | 6.0 | 4758 | 0.2454 | 70.6502 |
0.1526 | 7.0 | 5551 | 0.2439 | 74.9635 |
0.1382 | 8.0 | 6344 | 0.2515 | 66.4018 |
0.1241 | 9.0 | 7137 | 0.2559 | 66.8721 |
0.1138 | 10.0 | 7930 | 0.2692 | 65.8991 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-tiny