This model is a fine-tuned version of openai/whisper-medium on the Assemgamal955/egyptian-english-translation dataset. It achieves the following results on the evaluation set:

Loss: 1.0455
Model Preparation Time: 0.0097
Bleu: 15.6463

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: 2e-06
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 50
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Bleu
1.6186	1.0	1563	1.0344	0.0097	16.9977

Framework versions

Transformers 4.53.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2

AssemGamal955/OUTPUT_DIR2

Whisper Medium Egyptian Arabic --> english Translation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

AssemGamal955/
OUTPUT_DIR2