---
library_name: peft
language:
- ms
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- clt013/malay-speech-3k-rows-dataset_v2
model-index:
- name: Whisper Large v3 FT Malay - CLT013
  results: []
---

<!-- 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 Large v3 FT Malay - CLT013

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Malay Speech 3k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4149

## 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: 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 2.6257        | 0.3731  | 100  | 2.4258          |
| 2.3394        | 0.7463  | 200  | 1.7629          |
| 1.5256        | 1.1194  | 300  | 1.1983          |
| 1.0648        | 1.4925  | 400  | 0.9111          |
| 0.7458        | 1.8657  | 500  | 0.5754          |
| 0.5287        | 2.2388  | 600  | 0.5316          |
| 1.0221        | 2.6119  | 700  | 1.6308          |
| 0.9045        | 2.9851  | 800  | 0.4655          |
| 0.3766        | 3.3582  | 900  | 0.4186          |
| 0.3767        | 3.7313  | 1000 | 0.4082          |
| 0.355         | 4.1045  | 1100 | 0.4022          |
| 0.3284        | 4.4776  | 1200 | 0.3996          |
| 0.3229        | 4.8507  | 1300 | 0.3928          |
| 0.318         | 5.2239  | 1400 | 0.3925          |
| 0.3083        | 5.5970  | 1500 | 0.3905          |
| 0.3035        | 5.9701  | 1600 | 0.3900          |
| 0.2792        | 6.3433  | 1700 | 0.3897          |
| 0.2948        | 6.7164  | 1800 | 0.3872          |
| 0.2537        | 7.0896  | 1900 | 0.3869          |
| 0.2703        | 7.4627  | 2000 | 0.3907          |
| 0.2696        | 7.8358  | 2100 | 0.3891          |
| 0.2672        | 8.2090  | 2200 | 0.3923          |
| 0.2645        | 8.5821  | 2300 | 0.3900          |
| 0.2419        | 8.9552  | 2400 | 0.3894          |
| 0.2361        | 9.3284  | 2500 | 0.3928          |
| 0.2361        | 9.7015  | 2600 | 0.3915          |
| 0.2229        | 10.0746 | 2700 | 0.3922          |
| 0.2151        | 10.4478 | 2800 | 0.3962          |
| 0.248         | 10.8209 | 2900 | 0.3945          |
| 0.2152        | 11.1940 | 3000 | 0.3981          |
| 0.2144        | 11.5672 | 3100 | 0.4012          |
| 0.2278        | 11.9403 | 3200 | 0.3970          |
| 0.2017        | 12.3134 | 3300 | 0.4002          |
| 0.216         | 12.6866 | 3400 | 0.4018          |
| 0.2166        | 13.0597 | 3500 | 0.4013          |
| 0.2176        | 13.4328 | 3600 | 0.4043          |
| 0.2002        | 13.8060 | 3700 | 0.4054          |
| 0.1752        | 14.1791 | 3800 | 0.4066          |
| 0.1892        | 14.5522 | 3900 | 0.4048          |
| 0.2121        | 14.9254 | 4000 | 0.4078          |
| 0.209         | 15.2985 | 4100 | 0.4069          |
| 0.1857        | 15.6716 | 4200 | 0.4079          |
| 0.1867        | 16.0448 | 4300 | 0.4097          |
| 0.1833        | 16.4179 | 4400 | 0.4093          |
| 0.1918        | 16.7910 | 4500 | 0.4130          |
| 0.1815        | 17.1642 | 4600 | 0.4123          |
| 0.1854        | 17.5373 | 4700 | 0.4135          |
| 0.181         | 17.9104 | 4800 | 0.4131          |
| 0.1756        | 18.2836 | 4900 | 0.4130          |
| 0.177         | 18.6567 | 5000 | 0.4143          |
| 0.1829        | 19.0299 | 5100 | 0.4137          |
| 0.1809        | 19.4030 | 5200 | 0.4163          |
| 0.1777        | 19.7761 | 5300 | 0.4149          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1