| edge_features: | |
| use_bidirectional_edges: true | |
| features: | |
| lexical_feature_dim: 100000 | |
| inference: | |
| checkpoint_dir: experiments | |
| experiment_name: null | |
| loss: | |
| label_smoothing: 0.0 | |
| use_pos_weight: true | |
| model: | |
| dropout: 0.1 | |
| hidden_dim: 64 | |
| num_classes: 1 | |
| num_heads: 4 | |
| num_layers: 4 | |
| share_weights: false | |
| type: gatv2 | |
| training: | |
| accumulate_grad_batches: 1 | |
| annotations_dir: annotations_new | |
| batch_size: 128 | |
| deterministic: false | |
| gradient_clip_algorithm: norm | |
| gradient_clip_val: 0.5 | |
| learning_rate: 0.001 | |
| log_every_n_steps: 50 | |
| max_steps: 10000 | |
| num_workers: 4 | |
| optimizer: | |
| type: adamw | |
| weight_decay: 0.001 | |
| patience: 10 | |
| project_name: mecari | |
| seed: 42 | |
| use_wandb: true | |
| val_check_interval: 1.0 | |
| warmup_start_lr: 0.0 | |
| warmup_steps: 500 | |