metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-khmer-aug-v6-2
results: []
whisper-small-khmer-aug-v6-2
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: 0.3497
- Wer: 68.6233
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 |
---|---|---|---|---|
0.8376 | 0.9994 | 837 | 0.4499 | 100.4702 |
0.3482 | 2.0 | 1675 | 0.3490 | 79.3903 |
0.2732 | 2.9994 | 2512 | 0.3141 | 74.6230 |
0.231 | 4.0 | 3350 | 0.3190 | 75.0608 |
0.2002 | 4.9994 | 4187 | 0.3118 | 72.5799 |
0.1743 | 6.0 | 5025 | 0.3104 | 72.2556 |
0.1553 | 6.9994 | 5862 | 0.3216 | 71.2826 |
0.1375 | 8.0 | 6700 | 0.3307 | 73.7311 |
0.1217 | 8.9994 | 7537 | 0.3497 | 69.3854 |
0.1089 | 9.9940 | 8370 | 0.3497 | 68.6233 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1