---
language:
- eng
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- fyp
metrics:
- wer
model-index:
- name: Whisper Fine tuned Small
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Fyp Dataset
      type: fyp
      args: 'config: eng, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 11.272359095511305
---

<!-- 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 Fine tuned Small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Fyp Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1965
- Wer: 11.2724

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 102
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1398        | 0.4   | 20   | 0.2211          | 13.1623 |
| 0.0941        | 0.8   | 40   | 0.2144          | 11.8124 |
| 0.048         | 1.2   | 60   | 0.1997          | 11.2386 |
| 0.0481        | 1.6   | 80   | 0.1979          | 11.3736 |
| 0.0337        | 2.0   | 100  | 0.1965          | 11.2724 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1