metadata
library_name: keras-hub
This is a EfficientNet model uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
This model is related to a ImageClassifier task.
Model config:
- name: efficient_net_backbone
- trainable: True
- stackwise_width_coefficients: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
- stackwise_depth_coefficients: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
- dropout: 0
- depth_divisor: 8
- min_depth: None
- activation: silu
- input_shape: [None, None, 3]
- stackwise_kernel_sizes: [3, 3, 3, 3, 3, 3]
- stackwise_num_repeats: [2, 4, 4, 6, 9, 15]
- stackwise_input_filters: [24, 24, 48, 64, 128, 160]
- stackwise_output_filters: [24, 48, 64, 128, 160, 272]
- stackwise_expansion_ratios: [1, 4, 4, 4, 6, 6]
- stackwise_squeeze_and_excite_ratios: [0, 0, 0, 0.25, 0.25, 0.25]
- stackwise_strides: [1, 2, 2, 2, 1, 2]
- stackwise_block_types: ['fused', 'fused', 'fused', 'unfused', 'unfused', 'unfused']
- stackwise_force_input_filters: [0, 0, 0, 0, 0, 0]
- include_stem_padding: True
- use_depth_divisor_as_min_depth: True
- cap_round_filter_decrease: True
- stem_conv_padding: valid
- batch_norm_momentum: 0.9
- batch_norm_epsilon: 1e-05
- projection_activation: None
This model card has been generated automatically and should be completed by the model author. See Model Cards documentation for more information.