---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- asr-fyp
- generated_from_trainer
datasets:
- AshtonLKY/Whisper_ASR_ATC
metrics:
- wer
model-index:
- name: Whisper_ASR_ATC
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: AshtonLKY/augmented_audio
      type: AshtonLKY/Whisper_ASR_ATC
      args: 'split: test'
    metrics:
    - name: Wer
      type: wer
      value: 10.259091588129461
---

<!-- 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_ASR_ATC

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the AshtonLKY/augmented_audio dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0171
- Wer: 10.2591

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2282        | 0.3   | 1000  | 0.2253          | 49.5224 |
| 0.1461        | 0.6   | 2000  | 0.1456          | 42.3271 |
| 0.1052        | 0.89  | 3000  | 0.1061          | 10.8325 |
| 0.0698        | 1.19  | 4000  | 0.0708          | 13.8258 |
| 0.043         | 1.49  | 5000  | 0.0537          | 11.0072 |
| 0.0407        | 1.79  | 6000  | 0.0383          | 10.9401 |
| 0.019         | 2.08  | 7000  | 0.0349          | 15.2078 |
| 0.0323        | 2.38  | 8000  | 0.0268          | 11.4068 |
| 0.0164        | 2.68  | 9000  | 0.0236          | 12.3902 |
| 0.0153        | 2.98  | 10000 | 0.0171          | 10.2591 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0