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results_comparison_20250826_002710/execution_log.txt

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+Execução iniciada em: Tue Aug 26 00:27:10     2025
+
+
+=== ESTRATÉGIA: fedavg ===
+Início: Tue Aug 26 00:27:10     2025
+Status: SUCESSO
+Fim: Tue Aug 26 00:30:19     2025
+
+
+=== ESTRATÉGIA: fedadam ===
+Início: Tue Aug 26 00:30:25     2025
+Status: SUCESSO
+Fim: Tue Aug 26 00:33:24     2025
+
+
+=== ESTRATÉGIA: fedyogi ===
+Início: Tue Aug 26 00:33:29     2025
+Status: SUCESSO
+Fim: Tue Aug 26 00:36:36     2025
+
+
+=== ESTRATÉGIA: fedadagrad ===
+Início: Tue Aug 26 00:36:42     2025
+Status: SUCESSO
+Fim: Tue Aug 26 00:39:45     2025
+Execução finalizada em: Tue Aug 26 00:39:54     2025

results_comparison_20250826_002710/fedadagrad/analysis_fedadagrad.json

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results_comparison_20250826_002710/fedadagrad/analysis_fedadam.json

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results_comparison_20250826_002710/fedadagrad/analysis_fedavg.json

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results_comparison_20250826_002710/fedadagrad/analysis_fedyogi.json

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results_comparison_20250826_002710/fedadagrad/client_1_fedadagrad.log

@@ -0,0 +1,243 @@
+WARNING :   DEPRECATED FEATURE: flwr.client.start_client() is deprecated.
+	Instead, use the `flower-supernode` CLI command to start a SuperNode as shown below:
+
+		$ flower-supernode --insecure --superlink='<IP>:<PORT>'
+
+	To view all available options, run:
+
+		$ flower-supernode --help
+
+	Using `start_client()` is deprecated.
+
+            This is a deprecated feature. It will be removed
+            entirely in future versions of Flower.
+        
+INFO :      
+INFO :      Received: train message 4af737b7-d379-449f-b436-78001a125731
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message cf531bf8-f1c5-4b92-bd17-ceed4017fbb7
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+INFO :      Received: train message a4580f36-9da3-4702-b8cd-353f998cf9bb
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+INFO :      
+INFO :      Received: reconnect message ea85f68d-1b19-40e0-b26a-358082c79ae7
+INFO :      Disconnect and shut down
+Carregando dados para o cliente 1...
+Dispositivo: cpu
+Dados carregados: 626 batches de treino, 155 batches de teste
+Criando modelo LSTM para prever 10 passos.
+
+==================================================
+Iniciando cliente 1
+Conectando ao servidor em 127.0.0.1:8080
+Modelo: LSTM com 12110 par�metros
+==================================================
+
+
+[Cliente 1] === Rodada 1 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.013052
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 14.030549
+
+[Cliente 1] === Rodada 2 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 13.069769
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
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+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.813261
+
+[Cliente 1] === Rodada 3 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.312650
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
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+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
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+
+[Cliente 1] === Rodada 4 ===
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+
+[Cliente 1] === Rodada 5 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.018641
+[Cliente 1] Checkpoint salvo: metrics\client_1\model_round_5.pt
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+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
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+
+[Cliente 1] === Rodada 6 ===
+[Cliente 1] Iniciando treinamento...
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+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.047969
+
+[Cliente 1] === Rodada 7 ===
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+[Cliente 1] Perda de treinamento local: 0.022181
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+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.124156
+
+[Cliente 1] === Rodada 8 ===
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+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.187988
+
+[Cliente 1] === Rodada 9 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.031499
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
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+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.148241
+
+[Cliente 1] === Rodada 10 ===
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+[Cliente 1] Checkpoint salvo: metrics\client_1\model_round_10.pt
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+
+[Cliente 1] === Rodada 11 ===
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+[Cliente 1] === Rodada 12 ===
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+[Cliente 1] === Rodada 13 ===
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+[Cliente 1] === Rodada 14 ===
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+[Cliente 1] Perda de valida��o: 0.110763
+
+[Cliente 1] === Rodada 15 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.015980
+[Cliente 1] Checkpoint salvo: metrics\client_1\model_round_15.pt
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.020105
+
+[Cliente 1] Finalizado. M�tricas salvas em metrics\client_1

results_comparison_20250826_002710/fedadagrad/client_2_fedadagrad.log

@@ -0,0 +1,243 @@
+WARNING :   DEPRECATED FEATURE: flwr.client.start_client() is deprecated.
+	Instead, use the `flower-supernode` CLI command to start a SuperNode as shown below:
+
+		$ flower-supernode --insecure --superlink='<IP>:<PORT>'
+
+	To view all available options, run:
+
+		$ flower-supernode --help
+
+	Using `start_client()` is deprecated.
+
+            This is a deprecated feature. It will be removed
+            entirely in future versions of Flower.
+        
+INFO :      
+INFO :      Received: train message 79b550ae-f7f9-40b0-abb1-8c4e5b7e6524
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 54e81a09-5fb9-4af7-858a-fd104686b9ef
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 660f5f37-fce6-4008-9a09-ba554c9be75e
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+INFO :      
+INFO :      Received: evaluate message 7fd4e9bc-df8b-4018-8e5e-d7a3a3377e84
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+INFO :      
+INFO :      Received: train message a599ed8d-1971-4f02-92f2-2fadedfdf9f3
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+INFO :      
+INFO :      Received: evaluate message e8d5ba41-a516-4124-a8ac-da32ba58ec2b
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 1fd50d2f-a5fe-4b3d-ae8f-4124d7b3613f
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+INFO :      
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+INFO :      
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+INFO :      
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+INFO :      
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+INFO :      
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+INFO :      
+INFO :      Received: train message ab4697aa-ffae-4240-a859-bbaa28f8b261
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+INFO :      
+INFO :      Received: evaluate message eb56b352-a77a-4bee-9504-8e1cd4493839
+INFO :      Sent reply
+INFO :      
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+INFO :      
+INFO :      Received: train message 2d949c38-7035-4a6d-b15b-0e68509846db
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+INFO :      
+INFO :      Received: evaluate message bff7714f-0841-4f6e-983b-05f3e48f065d
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+INFO :      
+INFO :      Received: train message 5368cc6c-0e89-4837-9d59-b055dbb2138e
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+INFO :      
+INFO :      Received: evaluate message 91f157c6-866e-40ea-b501-d280afc09749
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+INFO :      
+INFO :      Received: train message b86ec98e-6c73-45d6-a74e-e035c0a98bec
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message e6f07db6-a31f-4601-a1f2-c70a9312fdd5
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+INFO :      
+INFO :      Received: train message ecc51e13-ae3a-4c5d-95fc-e481ea9b4086
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 10e00fee-edf4-4952-931c-8a228ee91ee7
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message cf71a2ba-0a46-4f0f-a42e-830dac6cbc6d
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 3724be57-bb00-4bd8-8508-33faadac190d
+INFO :      Sent reply
+INFO :      
+INFO :      Received: reconnect message b9396618-6eee-4384-9070-a2a63495784f
+INFO :      Disconnect and shut down
+Carregando dados para o cliente 2...
+Dispositivo: cpu
+Dados carregados: 792 batches de treino, 197 batches de teste
+Criando modelo LSTM para prever 10 passos.
+
+==================================================
+Iniciando cliente 2
+Conectando ao servidor em 127.0.0.1:8080
+Modelo: LSTM com 12110 par�metros
+==================================================
+
+
+[Cliente 2] === Rodada 1 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.006012
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 14.086604
+
+[Cliente 2] === Rodada 2 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 12.885653
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.872042
+
+[Cliente 2] === Rodada 3 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.402296
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.486267
+
+[Cliente 2] === Rodada 4 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.071917
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.045369
+
+[Cliente 2] === Rodada 5 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.011500
+[Cliente 2] Checkpoint salvo: metrics\client_2\model_round_5.pt
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.051305
+
+[Cliente 2] === Rodada 6 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.020807
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.075303
+
+[Cliente 2] === Rodada 7 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.019108
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.117011
+
+[Cliente 2] === Rodada 8 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.073632
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.132414
+
+[Cliente 2] === Rodada 9 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.018621
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.152679
+
+[Cliente 2] === Rodada 10 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.094948
+[Cliente 2] Checkpoint salvo: metrics\client_2\model_round_10.pt
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.009358
+
+[Cliente 2] === Rodada 11 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.003344
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.035432
+
+[Cliente 2] === Rodada 12 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.018202
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.080192
+
+[Cliente 2] === Rodada 13 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.048766
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.040772
+
+[Cliente 2] === Rodada 14 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.008924
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.112198
+
+[Cliente 2] === Rodada 15 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.008790
+[Cliente 2] Checkpoint salvo: metrics\client_2\model_round_15.pt
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.012933
+
+[Cliente 2] Finalizado. M�tricas salvas em metrics\client_2

results_comparison_20250826_002710/fedadagrad/client_3_fedadagrad.log

@@ -0,0 +1,243 @@
+WARNING :   DEPRECATED FEATURE: flwr.client.start_client() is deprecated.
+	Instead, use the `flower-supernode` CLI command to start a SuperNode as shown below:
+
+		$ flower-supernode --insecure --superlink='<IP>:<PORT>'
+
+	To view all available options, run:
+
+		$ flower-supernode --help
+
+	Using `start_client()` is deprecated.
+
+            This is a deprecated feature. It will be removed
+            entirely in future versions of Flower.
+        
+INFO :      
+INFO :      Received: train message 25853b85-8b12-472c-8dca-eac16db9f48c
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 2f181325-0a4e-4fee-a259-0468d8c4f978
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message bb19d6a6-e9e6-488d-906a-4d4965641d80
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message ccf24c7e-80c4-49c2-9728-cd278c065c97
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message d82653e6-4afa-4782-bdf8-25b4a4c85349
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+INFO :      
+INFO :      Received: evaluate message a08196a9-72c5-49f9-962b-3e1cd14280cf
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+INFO :      
+INFO :      Received: train message a802326c-d095-4991-8e87-778d7c37f7ca
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+INFO :      Received: train message 33467b70-a097-43d1-aa68-9db8c78a43ee
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+INFO :      
+INFO :      Received: evaluate message 63ef4e59-9636-4ded-9481-f883c44b2a3e
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 0b908abd-1299-4930-b2f9-4c80d97bdd3f
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 0146f3db-1ef2-496a-b629-8a5d1d5e82a7
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 63d6ded6-334d-4807-a5ad-ef336281c7ff
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message f487e001-8902-4e0c-a5ac-da352ae0ec6e
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 7b3bd506-55eb-4a4c-8d44-9a93630e1bef
+INFO :      Sent reply
+INFO :      
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+INFO :      Sent reply
+INFO :      
+INFO :      Received: reconnect message 39496e11-b6cf-4368-92f3-3b75a22299dd
+INFO :      Disconnect and shut down
+Carregando dados para o cliente 3...
+Dispositivo: cpu
+Dados carregados: 995 batches de treino, 247 batches de teste
+Criando modelo LSTM para prever 10 passos.
+
+==================================================
+Iniciando cliente 3
+Conectando ao servidor em 127.0.0.1:8080
+Modelo: LSTM com 12110 par�metros
+==================================================
+
+
+[Cliente 3] === Rodada 1 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.054918
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 13.667392
+
+[Cliente 3] === Rodada 2 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 12.082727
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.907519
+
+[Cliente 3] === Rodada 3 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.401098
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.591532
+
+[Cliente 3] === Rodada 4 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.255355
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.054797
+
+[Cliente 3] === Rodada 5 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.051430
+[Cliente 3] Checkpoint salvo: metrics\client_3\model_round_5.pt
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.066734
+
+[Cliente 3] === Rodada 6 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.023613
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.088038
+
+[Cliente 3] === Rodada 7 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.024161
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.178260
+
+[Cliente 3] === Rodada 8 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.112388
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.065086
+
+[Cliente 3] === Rodada 9 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.044495
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.085340
+
+[Cliente 3] === Rodada 10 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.053957
+[Cliente 3] Checkpoint salvo: metrics\client_3\model_round_10.pt
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.074286
+
+[Cliente 3] === Rodada 11 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.023814
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.050791
+
+[Cliente 3] === Rodada 12 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.035430
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.118169
+
+[Cliente 3] === Rodada 13 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.075215
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.064508
+
+[Cliente 3] === Rodada 14 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.021996
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.110286
+
+[Cliente 3] === Rodada 15 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.010951
+[Cliente 3] Checkpoint salvo: metrics\client_3\model_round_15.pt
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.038613
+
+[Cliente 3] Finalizado. M�tricas salvas em metrics\client_3

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results_comparison_20250826_002710/fedadagrad/server_fedadagrad.log

@@ -0,0 +1,288 @@
+WARNING :   DEPRECATED FEATURE: flwr.server.start_server() is deprecated.
+	Instead, use the `flower-superlink` CLI command to start a SuperLink as shown below:
+
+		$ flower-superlink --insecure
+
+	To view usage and all available options, run:
+
+		$ flower-superlink --help
+
+	Using `start_server()` is deprecated.
+
+            This is a deprecated feature. It will be removed
+            entirely in future versions of Flower.
+        
+INFO :      Starting Flower server, config: num_rounds=15, no round_timeout
+INFO :      Flower ECE: gRPC server running (15 rounds), SSL is disabled
+INFO :      [INIT]
+INFO :      Using initial global parameters provided by strategy
+INFO :      Starting evaluation of initial global parameters
+INFO :      Evaluation returned no results (`None`)
+INFO :      
+INFO :      [ROUND 1]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 2]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 3]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 4]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 5]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 6]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 7]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 8]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 9]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 10]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 11]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 12]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 13]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 14]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [ROUND 15]
+INFO :      configure_fit: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      configure_evaluate: strategy sampled 3 clients (out of 3)
+INFO :      aggregate_evaluate: received 3 results and 0 failures
+INFO :      
+INFO :      [SUMMARY]
+INFO :      Run finished 15 round(s) in 170.68s
+INFO :      	History (loss, distributed):
+INFO :      		round 1: 13.898984541953068
+INFO :      		round 2: 0.8714815956603053
+INFO :      		round 3: 0.46738389523349705
+INFO :      		round 4: 0.049456566335233376
+INFO :      		round 5: 0.058375708066070724
+INFO :      		round 6: 0.07348892275902684
+INFO :      		round 7: 0.144152629692749
+INFO :      		round 8: 0.11899180346139518
+INFO :      		round 9: 0.12372286365301419
+INFO :      		round 10: 0.0377169890169681
+INFO :      		round 11: 0.04240731753867245
+INFO :      		round 12: 0.09760029172147179
+INFO :      		round 13: 0.052567451272520216
+INFO :      		round 14: 0.11103739642762966
+INFO :      		round 15: 0.025393411362206766
+INFO :      	History (metrics, distributed, fit):
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+INFO :      	                         (2, 13.069769001817297),
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+INFO :      	History (metrics, distributed, evaluate):
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+INFO :      	 'global_eval_loss': [(1, 13.89898469338058),
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+INFO :      	                      (14, 0.11103739557521128),
+INFO :      	                      (15, 0.025393411267872205)]}
+INFO :      
+Tamanho da Previs�o: 10
+
+============================================================
+SERVIDOR DE APRENDIZADO FEDERADO
+============================================================
+Estrat�gia: FEDADAGRAD
+Rodadas: 15
+Clientes m�nimos: 3
+============================================================
+
+Iniciando servidor FL...
+
+============================================================
+TREINAMENTO CONCLU�DO - GERANDO AN�LISES
+============================================================
+Visualiza��es salvas em results
+M�tricas detalhadas salvas em results\detailed_metrics_fedadagrad.csv
+An�lise estat�stica salva em results\analysis_fedadagrad.json
+
+============================================================
+RESUMO DO TREINAMENTO
+============================================================
+Perda inicial de treino: 0.028003
+Perda final de treino: 0.011546
+Melhoria no treino: 58.77%
+
+Perda inicial de valida��o: 13.898985
+Perda final de valida��o: 0.025393
+Melhoria na valida��o: 99.82%
+
+Desvio padr�o final entre clientes: 0.010819
+Converg�ncia: Moderada
+
+============================================================
+Resultados salvos em: results
+============================================================

results_comparison_20250826_002710/fedadagrad/summary_report.json

@@ -0,0 +1,124 @@
+{
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results_comparison_20250826_002710/fedadam/analysis_fedadam.json

@@ -0,0 +1,79 @@
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results_comparison_20250826_002710/fedadam/analysis_fedavg.json

@@ -0,0 +1,79 @@
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results_comparison_20250826_002710/fedadam/client_1_fedadam.log

@@ -0,0 +1,243 @@
+WARNING :   DEPRECATED FEATURE: flwr.client.start_client() is deprecated.
+	Instead, use the `flower-supernode` CLI command to start a SuperNode as shown below:
+
+		$ flower-supernode --insecure --superlink='<IP>:<PORT>'
+
+	To view all available options, run:
+
+		$ flower-supernode --help
+
+	Using `start_client()` is deprecated.
+
+            This is a deprecated feature. It will be removed
+            entirely in future versions of Flower.
+        
+INFO :      
+INFO :      Received: train message 6b8350cc-48a3-4481-b3d1-0d8a8aa72469
+INFO :      Sent reply
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+INFO :      Received: train message 0937bb71-5c0b-4a43-a815-95bc0ba66494
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+INFO :      
+INFO :      Received: train message 9699db34-5de1-4a4d-9c9a-7bddb71ac542
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+INFO :      
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+INFO :      
+INFO :      Received: reconnect message ca107438-38db-4468-bd8b-28347ed39782
+INFO :      Disconnect and shut down
+Carregando dados para o cliente 1...
+Dispositivo: cpu
+Dados carregados: 626 batches de treino, 155 batches de teste
+Criando modelo LSTM para prever 10 passos.
+
+==================================================
+Iniciando cliente 1
+Conectando ao servidor em 127.0.0.1:8080
+Modelo: LSTM com 12110 par�metros
+==================================================
+
+
+[Cliente 1] === Rodada 1 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.012764
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 5.850430
+
+[Cliente 1] === Rodada 2 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 5.111335
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.367460
+
+[Cliente 1] === Rodada 3 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.248214
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 1.498217
+
+[Cliente 1] === Rodada 4 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.721097
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.187131
+
+[Cliente 1] === Rodada 5 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.127278
+[Cliente 1] Checkpoint salvo: metrics\client_1\model_round_5.pt
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 2.183796
+
+[Cliente 1] === Rodada 6 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 1.102567
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 1.105663
+
+[Cliente 1] === Rodada 7 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.521111
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.315400
+
+[Cliente 1] === Rodada 8 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.220199
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.463407
+
+[Cliente 1] === Rodada 9 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.265799
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.316405
+
+[Cliente 1] === Rodada 10 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.140211
+[Cliente 1] Checkpoint salvo: metrics\client_1\model_round_10.pt
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 1.343452
+
+[Cliente 1] === Rodada 11 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.125330
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 1.393274
+
+[Cliente 1] === Rodada 12 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.164211
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.383865
+
+[Cliente 1] === Rodada 13 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.092206
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.102037
+
+[Cliente 1] === Rodada 14 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.069149
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.058008
+
+[Cliente 1] === Rodada 15 ===
+[Cliente 1] Iniciando treinamento...
+[Cliente 1] Perda de treinamento local: 0.016739
+[Cliente 1] Checkpoint salvo: metrics\client_1\model_round_15.pt
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Avaliando modelo...
+[Cliente 1] M�tricas salvas em metrics\client_1\metrics_history.json
+[Cliente 1] Perda de valida��o: 0.051513
+
+[Cliente 1] Finalizado. M�tricas salvas em metrics\client_1

results_comparison_20250826_002710/fedadam/client_2_fedadam.log

@@ -0,0 +1,243 @@
+WARNING :   DEPRECATED FEATURE: flwr.client.start_client() is deprecated.
+	Instead, use the `flower-supernode` CLI command to start a SuperNode as shown below:
+
+		$ flower-supernode --insecure --superlink='<IP>:<PORT>'
+
+	To view all available options, run:
+
+		$ flower-supernode --help
+
+	Using `start_client()` is deprecated.
+
+            This is a deprecated feature. It will be removed
+            entirely in future versions of Flower.
+        
+INFO :      
+INFO :      Received: train message fe10fabf-b5ac-4154-8c3e-8a9df4a24874
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+INFO :      
+INFO :      Received: evaluate message 03b23b29-5a7e-41aa-90ae-f36a30fd3e59
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 9a48f13b-a531-4543-b5ca-b830a6294aa2
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+INFO :      
+INFO :      Received: evaluate message 952a8819-1478-4f9c-b8d2-a0cfa1613c6c
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+INFO :      
+INFO :      Received: train message 141df452-c61e-46cc-a8d1-3fb00d2e6d15
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+INFO :      
+INFO :      Received: evaluate message da9b7dbe-aa8c-4242-9acb-3db9d6a09764
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+INFO :      
+INFO :      Received: train message b4b51c97-d613-49bd-aaf6-45db9c2ca0fb
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+INFO :      
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+INFO :      
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+INFO :      
+INFO :      Received: train message 0bb5c259-48f3-40be-b2db-c145267dc8c7
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+INFO :      
+INFO :      Received: evaluate message 828498bf-4328-4653-8a66-3ef6d4f4c11b
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+INFO :      
+INFO :      Received: train message 8a2c866f-2c78-4810-834b-e5e955800e60
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+INFO :      
+INFO :      Received: evaluate message e995c729-f242-4bde-bf52-eb476995ebb1
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 517e8aae-c3c4-4e32-a19e-86a7654ebe8f
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+INFO :      
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+INFO :      
+INFO :      Received: train message 8fc00be7-b140-471e-a8fe-54ef4b5c2a26
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+INFO :      
+INFO :      Received: evaluate message 91ac3988-cbc7-46c7-b0f0-afa103992125
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 491ff222-3e8f-4240-af91-2d8a64c8d3ba
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message d4937f0e-2853-4b43-8a0c-a75db59ae1df
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 31fe0915-0d73-49de-9dce-378eb28c1155
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 18fadb3b-f854-469b-af6e-e44c8d78f4fc
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 64eab3c4-5982-43d2-a601-1e84b81305d0
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 95d6faa2-e586-4eba-8512-401d2dff7dc3
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 3ef79771-02ce-41cc-a443-2a4f9970ea71
+INFO :      Sent reply
+INFO :      
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+INFO :      Sent reply
+INFO :      
+INFO :      Received: reconnect message 2116e935-4b51-4f8e-99ed-7a75c0deaed5
+INFO :      Disconnect and shut down
+Carregando dados para o cliente 2...
+Dispositivo: cpu
+Dados carregados: 792 batches de treino, 197 batches de teste
+Criando modelo LSTM para prever 10 passos.
+
+==================================================
+Iniciando cliente 2
+Conectando ao servidor em 127.0.0.1:8080
+Modelo: LSTM com 12110 par�metros
+==================================================
+
+
+[Cliente 2] === Rodada 1 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.005998
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 5.888486
+
+[Cliente 2] === Rodada 2 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 4.974390
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.387931
+
+[Cliente 2] === Rodada 3 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.279165
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 1.713500
+
+[Cliente 2] === Rodada 4 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.973157
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.333240
+
+[Cliente 2] === Rodada 5 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.155787
+[Cliente 2] Checkpoint salvo: metrics\client_2\model_round_5.pt
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 2.099407
+
+[Cliente 2] === Rodada 6 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 1.481017
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 1.090772
+
+[Cliente 2] === Rodada 7 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.790649
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.275442
+
+[Cliente 2] === Rodada 8 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.166337
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.535139
+
+[Cliente 2] === Rodada 9 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.191204
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.407861
+
+[Cliente 2] === Rodada 10 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.113346
+[Cliente 2] Checkpoint salvo: metrics\client_2\model_round_10.pt
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 1.101800
+
+[Cliente 2] === Rodada 11 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.089515
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 1.344100
+
+[Cliente 2] === Rodada 12 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.215949
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.339882
+
+[Cliente 2] === Rodada 13 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.070410
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.095456
+
+[Cliente 2] === Rodada 14 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.052379
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.050710
+
+[Cliente 2] === Rodada 15 ===
+[Cliente 2] Iniciando treinamento...
+[Cliente 2] Perda de treinamento local: 0.010308
+[Cliente 2] Checkpoint salvo: metrics\client_2\model_round_15.pt
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Avaliando modelo...
+[Cliente 2] M�tricas salvas em metrics\client_2\metrics_history.json
+[Cliente 2] Perda de valida��o: 0.051057
+
+[Cliente 2] Finalizado. M�tricas salvas em metrics\client_2

results_comparison_20250826_002710/fedadam/client_3_fedadam.log

@@ -0,0 +1,243 @@
+WARNING :   DEPRECATED FEATURE: flwr.client.start_client() is deprecated.
+	Instead, use the `flower-supernode` CLI command to start a SuperNode as shown below:
+
+		$ flower-supernode --insecure --superlink='<IP>:<PORT>'
+
+	To view all available options, run:
+
+		$ flower-supernode --help
+
+	Using `start_client()` is deprecated.
+
+            This is a deprecated feature. It will be removed
+            entirely in future versions of Flower.
+        
+INFO :      
+INFO :      Received: train message 23a0edf5-3013-4f29-9a5a-dabca67424f7
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 64d9daa5-87b8-4e8c-b23d-9b8e36c6041d
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message e05c0226-5312-4eb7-8d19-90b68a1d4309
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 3e887108-d6bb-4b55-9d3e-8563e2aa42b3
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message bd82411d-cc26-497a-b7d6-da1fcd336370
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+INFO :      
+INFO :      Received: evaluate message d2a979de-19d0-418f-87a7-305b940d6a25
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+INFO :      
+INFO :      Received: train message 26f50ceb-ad4b-4276-9341-63c9170cdcbd
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+INFO :      Received: evaluate message 34268ef7-415a-4331-b7d3-d5603298700a
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 32c20e44-dec9-44a5-8085-b8d911f74308
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+INFO :      
+INFO :      Received: evaluate message a3bd9604-eeb5-4290-8722-13350d9c7111
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+INFO :      
+INFO :      Received: train message 0d7023ec-35c9-4983-be55-86052a1f86e1
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+INFO :      
+INFO :      Received: evaluate message 9d89e355-ba33-43c7-9249-788bcc0e792c
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 0b843c2d-5243-4864-a0ab-5efaf91b40b8
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 334f4b34-8ee9-4a37-b0cb-bdfa84daed19
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message 9a5849ac-f7c8-4387-8d41-0dba90670a14
+INFO :      Sent reply
+INFO :      
+INFO :      Received: evaluate message 698b24d3-4496-4aeb-a0ba-986d3e17344d
+INFO :      Sent reply
+INFO :      
+INFO :      Received: train message ebdc0668-b3db-4b39-bf7f-4097e82f424f
+INFO :      Sent reply
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+INFO :      
+INFO :      Received: reconnect message 331f47ff-c356-4ed5-886a-4475b6803af3
+INFO :      Disconnect and shut down
+Carregando dados para o cliente 3...
+Dispositivo: cpu
+Dados carregados: 995 batches de treino, 247 batches de teste
+Criando modelo LSTM para prever 10 passos.
+
+==================================================
+Iniciando cliente 3
+Conectando ao servidor em 127.0.0.1:8080
+Modelo: LSTM com 12110 par�metros
+==================================================
+
+
+[Cliente 3] === Rodada 1 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.045356
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 5.652705
+
+[Cliente 3] === Rodada 2 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 4.420750
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.460490
+
+[Cliente 3] === Rodada 3 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.352118
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 1.662424
+
+[Cliente 3] === Rodada 4 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 1.243881
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.255865
+
+[Cliente 3] === Rodada 5 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.139335
+[Cliente 3] Checkpoint salvo: metrics\client_3\model_round_5.pt
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 1.786058
+
+[Cliente 3] === Rodada 6 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.879303
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.808861
+
+[Cliente 3] === Rodada 7 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.318019
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.308229
+
+[Cliente 3] === Rodada 8 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.267704
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 1.092746
+
+[Cliente 3] === Rodada 9 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.327815
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.862200
+
+[Cliente 3] === Rodada 10 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.256952
+[Cliente 3] Checkpoint salvo: metrics\client_3\model_round_10.pt
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 1.120491
+
+[Cliente 3] === Rodada 11 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.104487
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.378346
+
+[Cliente 3] === Rodada 12 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.166542
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 1.177245
+
+[Cliente 3] === Rodada 13 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.191198
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.144548
+
+[Cliente 3] === Rodada 14 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.091879
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.584778
+
+[Cliente 3] === Rodada 15 ===
+[Cliente 3] Iniciando treinamento...
+[Cliente 3] Perda de treinamento local: 0.304566
+[Cliente 3] Checkpoint salvo: metrics\client_3\model_round_15.pt
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Avaliando modelo...
+[Cliente 3] M�tricas salvas em metrics\client_3\metrics_history.json
+[Cliente 3] Perda de valida��o: 0.326069
+
+[Cliente 3] Finalizado. M�tricas salvas em metrics\client_3