whisper-small-SIT_16_07_26_0226 API & Inference Endpoint

More information needed

More information needed

More information needed

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
mixed_precision_training: Native AMP
label_smoothing_factor: 0.1

Table with columns: Training Loss, Epoch, Step, Validation Loss, Wer
Training Loss	Epoch	Step	Validation Loss	Wer
4.0404	1.0	181	1.4567	0.7952
2.8614	2.0	362	1.4317	0.4639
2.8367	3.0	543	1.4270	0.4639

More information needed

More information needed

More information needed

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
mixed_precision_training: Native AMP
label_smoothing_factor: 0.1

Table with columns: Training Loss, Epoch, Step, Validation Loss, Wer
Training Loss	Epoch	Step	Validation Loss	Wer
4.0404	1.0	181	1.4567	0.7952
2.8614	2.0	362	1.4317	0.4639
2.8367	3.0	543	1.4270	0.4639

whisper-small-SIT_16_07_26_0226