---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- rngzhi/cs3264-project
metrics:
- wer
model-index:
- name: Whipser Small - Singlish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: National Speech Corpus(partial)
      type: rngzhi/cs3264-project
    metrics:
    - name: Wer
      type: wer
      value: 5.379530430818327
---

<!-- 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. -->

# Whipser Small - Singlish

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the National Speech Corpus(partial) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2020
- Wer: 5.3795

## 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0068        | 5.01  | 500  | 0.1508          | 5.4137 |
| 0.001         | 11.01 | 1000 | 0.1691          | 5.0832 |
| 0.0003        | 16.02 | 1500 | 0.1769          | 5.1060 |
| 0.0006        | 22.01 | 2000 | 0.1840          | 5.0946 |
| 0.0005        | 28.0  | 2500 | 0.1891          | 5.1174 |
| 0.0003        | 33.02 | 3000 | 0.1933          | 5.2086 |
| 0.0005        | 39.01 | 3500 | 0.1962          | 5.2997 |
| 0.0002        | 45.0  | 4000 | 0.1991          | 5.3339 |
| 0.0002        | 50.02 | 4500 | 0.2010          | 5.3681 |
| 0.0003        | 56.01 | 5000 | 0.2020          | 5.3795 |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.1.dev0
- Tokenizers 0.15.2