---
base_model: openai/whisper-large-v3
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 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: 0.7194

## 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.5614        | 0.0933 | 25   | 2.6198          |
| 2.9109        | 0.1866 | 50   | 2.5967          |
| 2.5414        | 0.2799 | 75   | 2.5518          |
| 2.4919        | 0.3731 | 100  | 2.4742          |
| 2.5861        | 0.4664 | 125  | 2.3639          |
| 2.454         | 0.5597 | 150  | 2.2213          |
| 2.32          | 0.6530 | 175  | 2.0616          |
| 2.1081        | 0.7463 | 200  | 1.8668          |
| 1.7976        | 0.8396 | 225  | 1.6736          |
| 1.7597        | 0.9328 | 250  | 1.5280          |
| 1.469         | 1.0261 | 275  | 1.4172          |
| 1.4484        | 1.1194 | 300  | 1.3275          |
| 1.2641        | 1.2127 | 325  | 1.2592          |
| 1.1853        | 1.3060 | 350  | 1.1972          |
| 1.184         | 1.3993 | 375  | 1.1449          |
| 1.1733        | 1.4925 | 400  | 1.0964          |
| 1.0707        | 1.5858 | 425  | 1.0568          |
| 0.9975        | 1.6791 | 450  | 1.0172          |
| 0.9897        | 1.7724 | 475  | 0.9855          |
| 1.0223        | 1.8657 | 500  | 0.9524          |
| 0.875         | 1.9590 | 525  | 0.9232          |
| 0.9242        | 2.0522 | 550  | 0.8968          |
| 0.8829        | 2.1455 | 575  | 0.8709          |
| 0.8491        | 2.2388 | 600  | 0.8454          |
| 0.7793        | 2.3321 | 625  | 0.8236          |
| 0.7733        | 2.4254 | 650  | 0.7993          |
| 0.7085        | 2.5187 | 675  | 0.7787          |
| 0.7403        | 2.6119 | 700  | 0.7596          |
| 0.7019        | 2.7052 | 725  | 0.7415          |
| 0.722         | 2.7985 | 750  | 0.7309          |
| 0.6403        | 2.8918 | 775  | 0.7220          |
| 0.699         | 2.9851 | 800  | 0.7194          |


### Framework versions

- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1