whisper-tiny-khmer-aug-kcc
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: 0.6705
- Wer: 46.2523
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 |
---|---|---|---|---|
2.0089 | 1.0 | 810 | 0.8377 | 64.9564 |
0.8348 | 2.0 | 1620 | 0.6317 | 51.0793 |
0.6384 | 3.0 | 2430 | 0.5752 | 51.3541 |
0.5227 | 4.0 | 3240 | 0.5643 | 48.8592 |
0.4323 | 5.0 | 4050 | 0.5749 | 48.2771 |
0.3649 | 6.0 | 4860 | 0.5818 | 46.6970 |
0.3092 | 7.0 | 5670 | 0.6012 | 46.0317 |
0.2611 | 8.0 | 6480 | 0.6331 | 46.0643 |
0.2239 | 9.0 | 7290 | 0.6683 | 46.4222 |
0.1963 | 10.0 | 8100 | 0.6705 | 46.2523 |
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