Step Training Loss Validation Loss Wer 500 0.431500 0.412413 48.265244 1000 0.244500 0.230148 29.284654 1500 0.134300 0.122366 16.588772 2000 0.055800 0.069241 10.551493 2500 0.045700 0.035967 4.860615 3000 0.027900 0.024117 3.425524 3500 0.011000 0.016053 1.770495 4000 0.004800 0.011227 1.171166

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: 1000
training_steps: 5000
mixed_precision_training: Native AMP

Framework versions

Transformers 4.40.2
Pytorch 2.2.0
Datasets 2.19.1
Tokenizers 0.19.1

Cafet/whisper-large-final

whisper-large-final

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Framework versions

Cafet/
whisper-large-final