| optim = AdamW(model.parameters(), lr=5e-5, eps=1e-8) #tasa de aprendizaje | |
| # Se inicializa el cargador de datos para los datos de entrenamiento | |
| train_loader = DataLoader(train_dataset, batch_size=16, shuffle=True) | |
| for epoch in range(10): | |
| {'score': 0.7284889221191406, 'start': 14, 'end': 29, 'answer': 'serology tests,'} | |
| Precisi贸n del modelo ajustado: 0.8211654387139986 | |
| Epoch 0: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=1.87] | |
| Epoch 1: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=0.211] | |
| Epoch 2: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=1.95] | |
| Epoch 3: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=0.0322] | |
| Epoch 4: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=0.0229] | |
| Epoch 5: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=0.0271] | |
| Epoch 6: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=0.59] | |
| Epoch 7: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=0.0233] | |
| Epoch 8: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=0.00257] | |
| Epoch 9: 100%|鈻堚枅鈻堚枅鈻堚枅鈻堚枅鈻堚枅| 94/94 [00:57<00:00, 1.62it/s, loss=0.00663] | |