| optim = AdamW(model.parameters(), lr=5e-5) #tasa de aprendizaje | |
| # Se inicializa el cargador de datos para los datos de entrenamiento | |
| train_loader = DataLoader(train_dataset, batch_size=8, shuffle=True) | |
| for epoch in range(3): | |
| Epoch 0: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:58<00:00, 1.61it/s, loss=1.8] | |
| Epoch 1: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:58<00:00, 1.61it/s, loss=0.476] | |
| Epoch 2: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:58<00:00, 1.61it/s, loss=0.133] | |
| Epoch 3: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:58<00:00, 1.61it/s, loss=0.0961] | |
| Epoch 4: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:58<00:00, 1.61it/s, loss=0.115] | |
| Epoch 5: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:58<00:00, 1.61it/s, loss=0.131] | |
| Epoch 6: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:58<00:00, 1.61it/s, loss=0.111] | |
| Epoch 7: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:58<00:00, 1.61it/s, loss=0.0191] | |
| Epoch 8: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:58<00:00, 1.61it/s, loss=0.00245]] | |
| Precisi贸n del modelo ajustado: | |