metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-base.en
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - SLURP-dataset
metrics:
  - wer
model-index:
  - name: Whisper Base En - Youssef Tarek
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: SLURP
          type: SLURP-dataset
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 25.911065345784657

Whisper Base En - Youssef Tarek

This model is a fine-tuned version of openai/whisper-base.en on the SLURP dataset. It achieves the following results on the evaluation set:

Loss: 0.3891
Wer: 25.9111

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

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2462	1.39	1000	0.3726	25.4293
0.1183	2.78	2000	0.3571	24.0966
0.054	4.17	3000	0.3811	25.8318
0.0348	5.56	4000	0.3891	25.9111

Framework versions

Transformers 4.38.1
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.1