HDF5 file, superblock version 0
group /
	attribute backend = "tensorflow"
	attribute keras_version = "2.10.0"
	attribute model_config = "{\"class_name\": \"Functional\", \"config\": {\"name\": \"model_1\", \"layers\": [{\"class_name\": \"InputLayer\", \"config\": {\"batch_input_shape\": [null, null], \"dtype\": \"int32\", \"sparse\": false, \"ragged\": false, \"name\": \"input_2\"}, \"name\": \"input_2\", \"inbound_nodes\": []}, {\"class_name\": \"Embedding\", \"config\": {\"name\": \"embedding_1\", \"trainable\": true, \"batch_input_shape\": [null, 100], \"dtype\": \"float32\", \"input_dim\": 2000, \"output_dim\": 50, \"embeddings_initializer\": {\"class_name\": \"RandomUniform\", \"config\": {\"minval\": -0.05, \"maxval\": 0.05, \"seed\": null}}, \"embeddings_regularizer\": null, \"activity_regularizer\": null, \"embeddings_constraint\": null, \"mask_zero\": false, \"input_length\": 100}, \"name\": \"embedding_1\", \"inbound_nodes\": [[[\"input_2\", 0, 0, {}]]]}, {\"class_name\": \"Bidirectional\", \"config\": {\"name\": \"bidirectional_2\", \"trainable\": true, \"dtype\": \"float32\", \"layer\": {\"class_name\": \"LSTM\", \"config\": {\"name\": \"lstm_2\", \"trainable\": true, \"dtype\": \"float32\", \"return_sequences\": true, \"return_state\": false, \"go_backwards\": false, \"stateful\": false, \"unroll\": false, \"time_major\": false, \"units\": 64, \"activation\": \"tanh\", \"recurrent_activation\": \"sigmoid\", \"use_bias\": true, \"kernel_initializer\": {\"class_name\": \"GlorotUniform\", \"config\": {\"seed\": null}, \"shared_object_id\": 3}, \"recurrent_initializer\": {\"class_name\": \"Orthogonal\", \"config\": {\"gain\": 1.0, \"seed\": null}, \"shared_object_id\": 4}, \"bias_initializer\": {\"class_name\": \"Zeros\", \"config\": {}, \"shared_object_id\": 5}, \"unit_forget_bias\": true, \"kernel_regularizer\": null, \"recurrent_regularizer\": null, \"bias_regularizer\": null, \"activity_regularizer\": null, \"kernel_constraint\": null, \"recurrent_constraint\": null, \"bias_constraint\": null, \"dropout\": 0.0, \"recurrent_dropout\": 0.0, \"implementation\": 2}}, \"merge_mode\": \"concat\"}, \"name\": \"bidirectional_2\", \"inbound_nodes\": [[[\"embedding_1\", 0, 0, {}]]]}, {\"class_name\": \"Bidirectional\", \"config\": {\"name\": \"bidirectional_3\", \"trainable\": true, \"dtype\": \"float32\", \"layer\": {\"class_name\": \"LSTM\", \"config\": {\"name\": \"lstm_3\", \"trainable\": true, \"dtype\": \"float32\", \"return_sequences\": false, \"return_state\": false, \"go_backwards\": false, \"stateful\": false, \"unroll\": false, \"time_major\": false, \"units\": 64, \"activation\": \"tanh\", \"recurrent_activation\": \"sigmoid\", \"use_bias\": true, \"kernel_initializer\": {\"class_name\": \"GlorotUniform\", \"config\": {\"seed\": null}, \"shared_object_id\": 9}, \"recurrent_initializer\": {\"class_name\": \"Orthogonal\", \"config\": {\"gain\": 1.0, \"seed\": null}, \"shared_object_id\": 10}, \"bias_initializer\": {\"class_name\": \"Zeros\", \"config\": {}, \"shared_object_id\": 11}, \"unit_forget_bias\": true, \"kernel_regularizer\": null, \"recurrent_regularizer\": null, \"bias_regularizer\": null, \"activity_regularizer\": null, \"kernel_constraint\": null, \"recurrent_constraint\": null, \"bias_constraint\": null, \"dropout\": 0.0, \"recurrent_dropout\": 0.0, \"implementation\": 2}}, \"merge_mode\": \"concat\"}, \"name\": \"bidirectional_3\", \"inbound_nodes\": [[[\"bidirectional_2\", 0, 0, {}]]]}, {\"class_name\": \"Dense\", \"config\": {\"name\": \"dense_1\", \"trainable\": true, \"dtype\": \"float32\", \"units\": 3, \"activation\": \"softmax\", \"use_bias\": true, \"kernel_initializer\": {\"class_name\": \"GlorotUniform\", \"config\": {\"seed\": null}}, \"bias_initializer\": {\"class_name\": \"Zeros\", \"config\": {}}, \"kernel_regularizer\": null, \"bias_regularizer\": null, \"activity_regularizer\": null, \"kernel_constraint\": null, \"bias_constraint\": null}, \"name\": \"dense_1\", \"inbound_nodes\": [[[\"bidirectional_3\", 0, 0, {}]]]}], \"input_layers\": [[\"input_2\", 0, 0]], \"output_layers\": [[\"dense_1\", 0, 0]]}}"
	attribute training_config = "{\"loss\": \"sparse_categorical_crossentropy\", \"metrics\": [[{\"class_name\": \"MeanMetricWrapper\", \"config\": {\"name\": \"accuracy\", \"dtype\": \"float32\", \"fn\": \"sparse_categorical_accuracy\"}}]], \"weighted_metrics\": null, \"loss_weights\": null, \"optimizer_config\": {\"class_name\": \"Adam\", \"config\": {\"name\": \"Adam\", \"learning_rate\": 0.0010000000474974513, \"decay\": 0.0, \"beta_1\": 0.8999999761581421, \"beta_2\": 0.9990000128746033, \"epsilon\": 1e-07, \"amsgrad\": false}}}"
group /model_weights
	attribute backend = "tensorflow"
	attribute keras_version = "2.10.0"
	attribute layer_names = "input_2", "embedding_1", "bidirectional_2", "bidirectional_3", "dense_1"
group /model_weights/bidirectional_2
	attribute weight_names = "bidirectional_2/forward_lstm_2/lstm_cell_13/kernel:0", "bidirectional_2/forward_lstm_2/lstm_cell_13/recurrent_kernel:0", "bidirectional_2/forward_lstm_2/lstm_cell_13/bias:0", "bidirectional_2/backward_lstm_2/lstm_cell_14/kernel:0", "bidirectional_2/backward_lstm_2/lstm_cell_14/recurrent_kernel:0", "bidirectional_2/backward_lstm_2/lstm_cell_14/bias:0"
group /model_weights/bidirectional_2/bidirectional_2
group /model_weights/bidirectional_2/bidirectional_2/backward_lstm_2
group /model_weights/bidirectional_2/bidirectional_2/backward_lstm_2/lstm_cell_14
dataset /model_weights/bidirectional_2/bidirectional_2/backward_lstm_2/lstm_cell_14/bias:0: float32, shape (256)
dataset /model_weights/bidirectional_2/bidirectional_2/backward_lstm_2/lstm_cell_14/kernel:0: float32, shape (50, 256)
dataset /model_weights/bidirectional_2/bidirectional_2/backward_lstm_2/lstm_cell_14/recurrent_kernel:0: float32, shape (64, 256)
group /model_weights/bidirectional_2/bidirectional_2/forward_lstm_2
group /model_weights/bidirectional_2/bidirectional_2/forward_lstm_2/lstm_cell_13
dataset /model_weights/bidirectional_2/bidirectional_2/forward_lstm_2/lstm_cell_13/bias:0: float32, shape (256)
dataset /model_weights/bidirectional_2/bidirectional_2/forward_lstm_2/lstm_cell_13/kernel:0: float32, shape (50, 256)
dataset /model_weights/bidirectional_2/bidirectional_2/forward_lstm_2/lstm_cell_13/recurrent_kernel:0: float32, shape (64, 256)
group /model_weights/bidirectional_3
	attribute weight_names = "bidirectional_3/forward_lstm_3/lstm_cell_16/kernel:0", "bidirectional_3/forward_lstm_3/lstm_cell_16/recurrent_kernel:0", "bidirectional_3/forward_lstm_3/lstm_cell_16/bias:0", "bidirectional_3/backward_lstm_3/lstm_cell_17/kernel:0", "bidirectional_3/backward_lstm_3/lstm_cell_17/recurrent_kernel:0", "bidirectional_3/backward_lstm_3/lstm_cell_17/bias:0"
group /model_weights/bidirectional_3/bidirectional_3
group /model_weights/bidirectional_3/bidirectional_3/backward_lstm_3
group /model_weights/bidirectional_3/bidirectional_3/backward_lstm_3/lstm_cell_17
dataset /model_weights/bidirectional_3/bidirectional_3/backward_lstm_3/lstm_cell_17/bias:0: float32, shape (256)
dataset /model_weights/bidirectional_3/bidirectional_3/backward_lstm_3/lstm_cell_17/kernel:0: float32, shape (128, 256)
dataset /model_weights/bidirectional_3/bidirectional_3/backward_lstm_3/lstm_cell_17/recurrent_kernel:0: float32, shape (64, 256)
group /model_weights/bidirectional_3/bidirectional_3/forward_lstm_3
group /model_weights/bidirectional_3/bidirectional_3/forward_lstm_3/lstm_cell_16
dataset /model_weights/bidirectional_3/bidirectional_3/forward_lstm_3/lstm_cell_16/bias:0: float32, shape (256)
dataset /model_weights/bidirectional_3/bidirectional_3/forward_lstm_3/lstm_cell_16/kernel:0: float32, shape (128, 256)
dataset /model_weights/bidirectional_3/bidirectional_3/forward_lstm_3/lstm_cell_16/recurrent_kernel:0: float32, shape (64, 256)
group /model_weights/dense_1
	attribute weight_names = "dense_1/kernel:0", "dense_1/bias:0"
group /model_weights/dense_1/dense_1
dataset /model_weights/dense_1/dense_1/bias:0: float32, shape (3)
dataset /model_weights/dense_1/dense_1/kernel:0: float32, shape (128, 3)
group /model_weights/embedding_1
	attribute weight_names = "embedding_1/embeddings:0"
group /model_weights/embedding_1/embedding_1
dataset /model_weights/embedding_1/embedding_1/embeddings:0: float32, shape (2000, 50)
group /model_weights/input_2
	attribute weight_names = (float64, not shown)
group /model_weights/top_level_model_weights
	attribute weight_names = (float64, not shown)