metadata
language:
- ms
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- clt013/malay-speech-3k-rows-dataset
metrics:
- wer
model-index:
- name: Whisper Small FT Malay - CLT013
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Malay Speech 3k
type: clt013/malay-speech-3k-rows-dataset
config: default
split: train
args: default
metrics:
- name: Wer
type: wer
value: 27.169943
Whisper Small FT Malay - CLT013
This model is a fine-tuned version of openai/whisper-small on the Malay Speech 3k dataset. It achieves the following results on the evaluation set:
- Loss: 0.545344
- Wer: 27.169943
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7275 | 0.1 | 100 | 0.677592 | 38.9111 |
| 0.521 | 0.2 | 200 | 0.565486 | 36.6151 |
| 0.3128 | 0.3 | 300 | 0.525294 | 29.7965 |
| 0.2964 | 0.4 | 400 | 0.500519 | 35.2235 |
| 0.1631 | 0.5 | 500 | 0.508256 | 36.2845 |
| 0.0731 | 0.6 | 600 | 0.532225 | 38.4414 |
| 0.0548 | 0.7 | 700 | 0.519905 | 27.2743 |
| 0.0289 | 0.8 | 800 | 0.533013 | 27.6917 |
| 0.0131 | 0.9 | 900 | 0.548259 | 26.9090 |
| 0.0071 | 1.0 | 1000 | 0.545344 | 27.1699 |
Framework versions
- Transformers 4.41.2
- Datasets 2.19.1
- Tokenizers 0.19.1