| @@ -211,7 +211,7 @@ Out: | |||
| abl - INFO - Evaluation start: loop(val) [1] | |||
| abl - INFO - Evaluation ended, mnist_add/character_accuracy: 0.207 mnist_add/reasoning_accuracy: 0.245 | |||
| abl - INFO - Saving model: loop(save) [1] | |||
| abl - INFO - Checkpoints will be saved to results/20231217_14_27_56/weights/model_checkpoint_loop_1.pth | |||
| abl - INFO - Checkpoints will be saved to log_dir/weights/model_checkpoint_loop_1.pth | |||
| abl - INFO - loop(train) [2/5] segment(train) [1/3] | |||
| abl - INFO - model loss: 0.97430 | |||
| abl - INFO - loop(train) [2/5] segment(train) [2/3] | |||
| @@ -221,7 +221,7 @@ Out: | |||
| abl - INFO - Evaluation start: loop(val) [2] | |||
| abl - INFO - Evaluation ended, mnist_add/character_accuracy: 0.191 mnist_add/reasoning_accuracy: 0.353 | |||
| abl - INFO - Saving model: loop(save) [2] | |||
| abl - INFO - Checkpoints will be saved to results/20231217_14_27_56/weights/model_checkpoint_loop_2.pth | |||
| abl - INFO - Checkpoints will be saved to log_dir/weights/model_checkpoint_loop_2.pth | |||
| abl - INFO - loop(train) [3/5] segment(train) [1/3] | |||
| abl - INFO - model loss: 0.79906 | |||
| abl - INFO - loop(train) [3/5] segment(train) [2/3] | |||
| @@ -231,7 +231,7 @@ Out: | |||
| abl - INFO - Evaluation start: loop(val) [3] | |||
| abl - INFO - Evaluation ended, mnist_add/character_accuracy: 0.148 mnist_add/reasoning_accuracy: 0.385 | |||
| abl - INFO - Saving model: loop(save) [3] | |||
| abl - INFO - Checkpoints will be saved to results/20231217_14_27_56/weights/model_checkpoint_loop_3.pth | |||
| abl - INFO - Checkpoints will be saved to log_dir/weights/model_checkpoint_loop_3.pth | |||
| abl - INFO - loop(train) [4/5] segment(train) [1/3] | |||
| abl - INFO - model loss: 0.72659 | |||
| abl - INFO - loop(train) [4/5] segment(train) [2/3] | |||
| @@ -241,7 +241,7 @@ Out: | |||
| abl - INFO - Evaluation start: loop(val) [4] | |||
| abl - INFO - Evaluation ended, mnist_add/character_accuracy: 0.016 mnist_add/reasoning_accuracy: 0.494 | |||
| abl - INFO - Saving model: loop(save) [4] | |||
| abl - INFO - Checkpoints will be saved to results/20231217_14_27_56/weights/model_checkpoint_loop_4.pth | |||
| abl - INFO - Checkpoints will be saved to log_dir/weights/model_checkpoint_loop_4.pth | |||
| abl - INFO - loop(train) [5/5] segment(train) [1/3] | |||
| abl - INFO - model loss: 0.61140 | |||
| abl - INFO - loop(train) [5/5] segment(train) [2/3] | |||
| @@ -251,7 +251,7 @@ Out: | |||
| abl - INFO - Evaluation start: loop(val) [5] | |||
| abl - INFO - Evaluation ended, mnist_add/character_accuracy: 0.002 mnist_add/reasoning_accuracy: 0.507 | |||
| abl - INFO - Saving model: loop(save) [5] | |||
| abl - INFO - Checkpoints will be saved to results/20231217_14_27_56/weights/model_checkpoint_loop_5.pth | |||
| abl - INFO - Checkpoints will be saved to log_dir/weights/model_checkpoint_loop_5.pth | |||
| abl - INFO - Evaluation ended, mnist_add/character_accuracy: 0.002 mnist_add/reasoning_accuracy: 0.482 | |||
| More concrete examples are available in `examples/mnist_add` folder. | |||
| More concrete examples are available in ``examples/mnist_add`` folder. | |||