---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- Alsman68/CapstoneDataset1
metrics:
- wer
model-index:
- name: capstone-whisper-our-data-only
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Simulated Aviation Audio For Capstone
      type: Alsman68/CapstoneDataset1
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 52.44755244755245
---

<!-- 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. -->

# capstone-whisper-our-data-only

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Simulated Aviation Audio For Capstone dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9014
- Wer: 52.4476

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer     |
|:-------------:|:--------:|:----:|:---------------:|:-------:|
| 0.0001        | 71.4286  | 1000 | 1.6081          | 53.1469 |
| 0.0001        | 142.8571 | 2000 | 1.7786          | 52.6383 |
| 0.0           | 214.2857 | 3000 | 1.8591          | 52.3204 |
| 0.0           | 285.7143 | 4000 | 1.9014          | 52.4476 |


### Framework versions

- Transformers 4.50.1
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1