metadata
base_model: openai/whisper-small
datasets:
- clt013/malay-speech-3k-rows-dataset_v2
language:
- ms
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: Whisper Small FT Malay - CLT013
results: []
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: 0.6336
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: 0.001
- train_batch_size: 8
- 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: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1001 | 0.3731 | 100 | 0.8407 |
| 0.7305 | 0.7463 | 200 | 0.7879 |
| 0.615 | 1.1194 | 300 | 0.7401 |
| 0.4364 | 1.4925 | 400 | 0.7126 |
| 0.3951 | 1.8657 | 500 | 0.6772 |
| 0.2428 | 2.2388 | 600 | 0.6649 |
| 0.185 | 2.6119 | 700 | 0.6426 |
| 0.1781 | 2.9851 | 800 | 0.6336 |
Framework versions
- PEFT 0.13.1.dev0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1