|
--- |
|
language: |
|
- ms |
|
license: apache-2.0 |
|
base_model: openai/whisper-medium |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- clt013/malay-speech-1.6-million-rows-dataset |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Medium FT Malay - CLT013 |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Malay Speech 1.6 million |
|
type: clt013/malay-speech-1.6-million-rows-dataset |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 39.65666891696403 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Whisper Medium FT Malay - CLT013 |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Malay Speech 1.6 million dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7057 |
|
- Wer: 39.6567 |
|
|
|
## 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 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 50 |
|
- training_steps: 1000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 1.0434 | 0.1 | 100 | 0.9250 | 53.3417 | |
|
| 0.8131 | 0.2 | 200 | 0.8394 | 46.5908 | |
|
| 0.7852 | 0.3 | 300 | 0.8033 | 45.1635 | |
|
| 0.7643 | 0.4 | 400 | 0.7769 | 53.5732 | |
|
| 0.7424 | 0.5 | 500 | 0.7582 | 46.6969 | |
|
| 0.7406 | 0.6 | 600 | 0.7451 | 39.6760 | |
|
| 0.7913 | 0.7 | 700 | 0.7288 | 39.3866 | |
|
| 0.7452 | 0.8 | 800 | 0.7164 | 37.9979 | |
|
| 0.718 | 0.9 | 900 | 0.7099 | 38.7694 | |
|
| 0.7328 | 1.0 | 1000 | 0.7057 | 39.6567 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
