---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- Jzuluaga/atcosim_corpus
metrics:
- wer
model-index:
- name: Whisper Large - Whisper with atcosim_corpus
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: The ATCOSIM Air Traffic Control Simulation Speech corpus is a speech database
        of air traffic control (ATC) operator speech, provided by Graz University
        of Technology (TUG) and Eurocontrol Experimental Centre (EEC)
      type: Jzuluaga/atcosim_corpus
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.9495627594735447
---

<!-- 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 Large - Whisper with atcosim_corpus

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the The ATCOSIM Air Traffic Control Simulation Speech corpus is a speech database of air traffic control (ATC) operator speech, provided by Graz University of Technology (TUG) and Eurocontrol Experimental Centre (EEC) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0413
- Wer: 0.9496

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.012         | 2.0921 | 1000 | 0.0405          | 1.2543 |
| 0.0019        | 4.1841 | 2000 | 0.0372          | 1.0776 |
| 0.0001        | 6.2762 | 3000 | 0.0407          | 0.9716 |
| 0.0           | 8.3682 | 4000 | 0.0413          | 0.9496 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1