whisper-tiny-khmer-aug-kcc-v2
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: 0.6443
- Wer: 46.0250
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 |
|---|---|---|---|---|
| 1.8936 | 1.0 | 862 | 0.8037 | 61.5162 |
| 0.8143 | 2.0 | 1724 | 0.6129 | 55.2047 |
| 0.6306 | 3.0 | 2586 | 0.5592 | 46.5133 |
| 0.52 | 4.0 | 3448 | 0.5522 | 53.2805 |
| 0.4271 | 5.0 | 4310 | 0.5466 | 44.1696 |
| 0.3484 | 6.0 | 5172 | 0.5576 | 49.7975 |
| 0.2951 | 7.0 | 6034 | 0.5875 | 46.6725 |
| 0.2524 | 8.0 | 6896 | 0.6020 | 47.5767 |
| 0.2156 | 9.0 | 7758 | 0.6260 | 45.0557 |
| 0.1878 | 10.0 | 8620 | 0.6443 | 46.0250 |
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