| Training LSTM model... | |
| Epoch 1, Loss: 71.1234 | |
| Epoch 2, Loss: 68.6489 | |
| Epoch 3, Loss: 69.2523 | |
| Epoch 4, Loss: 68.8158 | |
| Epoch 5, Loss: 68.9286 | |
| precision recall f1-score support | |
| 0 0.00 0.00 0.00 165 | |
| 1 0.00 0.00 0.00 58 | |
| 2 0.66 1.00 0.79 430 | |
| accuracy 0.66 653 | |
| macro avg 0.22 0.33 0.26 653 | |
| weighted avg 0.43 0.66 0.52 653 | |
| Training GRU model... | |
| Epoch 1, Loss: 70.4632 | |
| Epoch 2, Loss: 69.1792 | |
| Epoch 3, Loss: 69.2010 | |
| Epoch 4, Loss: 68.6870 | |
| Epoch 5, Loss: 68.6591 | |
| precision recall f1-score support | |
| 0 0.00 0.00 0.00 165 | |
| 1 0.00 0.00 0.00 58 | |
| 2 0.66 1.00 0.79 430 | |
| accuracy 0.66 653 | |
| macro avg 0.22 0.33 0.26 653 | |
| weighted avg 0.43 0.66 0.52 653 | |
| Training CNN model... | |
| Epoch 1, Loss: 70.8052 | |
| Epoch 2, Loss: 62.6982 | |
| Epoch 3, Loss: 37.3597 | |
| Epoch 4, Loss: 8.0962 | |
| Epoch 5, Loss: 1.3354 | |
| precision recall f1-score support | |
| 0 0.47 0.42 0.45 165 | |
| 1 0.24 0.09 0.13 58 | |
| 2 0.72 0.81 0.77 430 | |
| accuracy 0.65 653 | |
| macro avg 0.48 0.44 0.45 653 | |
| weighted avg 0.62 0.65 0.63 653 |