---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- rngzhi/cs3264-project
metrics:
- wer
model-index:
- name: Whisper Small - Singlish v2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: rngzhi/cs3264-project
      type: rngzhi/cs3264-project
    metrics:
    - name: Wer
      type: wer
      value: 4.923638021426943
---

<!-- 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 Small - Singlish v2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the rngzhi/cs3264-project dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1850
- Wer: 4.9236

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- training_steps: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.5404        | 0.0625 | 50   | 0.1970          | 5.6075 |
| 0.075         | 1.0144 | 100  | 0.1557          | 4.8780 |
| 0.042         | 1.0769 | 150  | 0.1610          | 4.9692 |
| 0.0185        | 2.0288 | 200  | 0.1628          | 4.9122 |
| 0.0117        | 2.0913 | 250  | 0.1651          | 5.0262 |
| 0.0096        | 3.0431 | 300  | 0.1716          | 5.0490 |
| 0.007         | 3.1056 | 350  | 0.1747          | 5.0034 |
| 0.0045        | 4.0575 | 400  | 0.1783          | 5.1402 |
| 0.0046        | 5.0094 | 450  | 0.1749          | 5.1288 |
| 0.004         | 5.0719 | 500  | 0.1782          | 5.0148 |
| 0.0021        | 6.0237 | 550  | 0.1814          | 5.0034 |
| 0.004         | 6.0862 | 600  | 0.1813          | 4.9920 |
| 0.0024        | 7.0381 | 650  | 0.1844          | 4.9350 |
| 0.0022        | 7.1006 | 700  | 0.1834          | 4.9008 |
| 0.0032        | 8.0525 | 750  | 0.1850          | 4.9236 |
| 0.0016        | 9.0044 | 800  | 0.1850          | 4.9236 |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.1.dev0
- Tokenizers 0.19.1