metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-large
tags:
  - generated_from_trainer
datasets:
  - jlvdoorn/atco2-asr-atcosim
metrics:
  - wer
model-index:
  - name: Whisper Large - Whisper with atco2-asr-atcosim
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: >-
            This is a dataset constructed from two datasets: ATCO2-ASR and
            ATCOSIM.
          type: jlvdoorn/atco2-asr-atcosim
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 2.642174131857071

Whisper Large - Whisper with atco2-asr-atcosim

This model is a fine-tuned version of openai/whisper-large on the This is a dataset constructed from two datasets: ATCO2-ASR and ATCOSIM. dataset. It achieves the following results on the evaluation set:

Loss: 0.0715
Wer: 2.6422

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
0.0547	1.9763	1000	0.0675	4.0346
0.0115	3.9526	2000	0.0690	2.8309
0.003	5.9289	3000	0.0682	2.6212
0.0003	7.9051	4000	0.0715	2.6422

Framework versions

Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1