---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small FT Malay - CLT013

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./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