whisper-small-khmer-aug-v6
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2209
- Wer: 60.8400
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 |
---|---|---|---|---|
0.5473 | 0.9994 | 837 | 0.2368 | 79.1309 |
0.2005 | 2.0 | 1675 | 0.1907 | 69.7422 |
0.1505 | 2.9994 | 2512 | 0.1775 | 65.4289 |
0.1221 | 4.0 | 3350 | 0.1839 | 65.3802 |
0.1013 | 4.9994 | 4187 | 0.1888 | 64.1641 |
0.0851 | 6.0 | 5025 | 0.1921 | 62.8507 |
0.0725 | 6.9994 | 5862 | 0.1960 | 61.9588 |
0.0618 | 8.0 | 6700 | 0.2103 | 62.6074 |
0.053 | 8.9994 | 7537 | 0.2161 | 61.3426 |
0.0474 | 9.9940 | 8370 | 0.2209 | 60.8400 |
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-small