This model is a fine-tuned version of distil-whisper/distil-large-v2 on the nadsoft/Jordan-Audio dataset. It achieves the following results on the evaluation set:

Loss: 0.9732
Wer Ortho: 47.5105
Wer: 45.2234

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: 0.0002
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 8000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.2094	7.04	2000	0.8198	48.5575	46.3918
0.0883	14.08	4000	0.9112	47.4174	44.6048
0.0662	21.13	6000	0.9644	46.8125	44.6277
0.0496	28.17	8000	0.9732	47.5105	45.2234

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1

Ahmed107/distill-ar

Hamsa distill alfa

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Ahmed107/
distill-ar