---
library_name: peft
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mesolitica/IMDA-TTS
metrics:
- wer
model-index:
- name: Whisper Small NSC small (500 steps) - Jarrett Er
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: NSC Small section
      type: mesolitica/IMDA-TTS
      split: None
      args: 'config: en, split: train'
    metrics:
    - type: wer
      value: 3.0164184803360063
      name: Wer
---

<!-- 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 NSC small (500 steps) - Jarrett Er

This model is a fine-tuned version of [Thecoder3281f/whisper-small-hi-commonvoice17-1000](https://huggingface.co/Thecoder3281f/whisper-small-hi-commonvoice17-1000) on the NSC Small section dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0777
- Wer: 3.0164

## 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: 0.0001
- train_batch_size: 16
- 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0822        | 0.8850 | 100  | 0.0686          | 3.0164 |
| 0.0585        | 1.7699 | 200  | 0.0700          | 3.0928 |
| 0.0317        | 2.6549 | 300  | 0.0726          | 3.0546 |
| 0.0184        | 3.5398 | 400  | 0.0781          | 3.2455 |
| 0.0194        | 4.4248 | 500  | 0.0777          | 3.0164 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.1.dev0
- Tokenizers 0.20.3