metadata
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-khmer-aug-v6
results: []
whisper-base-khmer-aug-v6
This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2379
- Wer: 62.5101
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 |
|---|---|---|---|---|
| 0.5956 | 0.9994 | 837 | 0.2717 | 78.0931 |
| 0.2404 | 2.0 | 1675 | 0.2206 | 79.6660 |
| 0.184 | 2.9994 | 2512 | 0.2061 | 68.4287 |
| 0.1511 | 4.0 | 3350 | 0.2001 | 66.4505 |
| 0.1288 | 4.9994 | 4187 | 0.2038 | 66.2883 |
| 0.1108 | 6.0 | 5025 | 0.2032 | 64.6506 |
| 0.0968 | 6.9994 | 5862 | 0.2098 | 64.0182 |
| 0.0842 | 8.0 | 6700 | 0.2180 | 63.5966 |
| 0.0739 | 8.9994 | 7537 | 0.2303 | 63.9857 |
| 0.065 | 9.9940 | 8370 | 0.2379 | 62.5101 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1