MGM2 / models /medium /config.json
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{
"abundance": {
"min_abundance": 0.0001,
"output_min": -2.0,
"output_max": 2.0,
"normalize": false,
"num_bins": 5,
"binning_method": "quantile",
"fixed_thresholds": [
0.0,
0.0001,
0.001,
0.01,
0.1
],
"enable_regression": true,
"regression_top_k_bins": 2
},
"model": {
"vocab_size": 10000,
"embedding_dim": 1536,
"hidden_size": 320,
"num_hidden_layers": 6,
"num_attention_heads": 5,
"intermediate_size": 1280,
"hidden_dropout_prob": 0.1,
"attention_probs_dropout_prob": 0.1,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 2048,
"pad_token_id": -1,
"cls_token_id": -1,
"mlp_dropout": 0.1
},
"loss": {
"lambda_bin": 1.0,
"lambda_regression": 0.3,
"bin_loss_type": "focal",
"regression_loss_type": "mse",
"focal_alpha": 0.25,
"focal_gamma": 2.0
},
"training": {
"mask_prob": 0.15,
"mask_ratio": [
0.8,
0.1,
0.1
],
"train_ratio": 0.9,
"val_ratio": 0.1,
"batch_size": 512,
"num_workers": 0,
"learning_rate": 5e-05,
"weight_decay": 0.01,
"warmup_steps": 1000,
"lr_scheduler": "warmup_cosine",
"min_lr_ratio": 0.1,
"max_epochs": 50,
"gradient_clip_val": 1.0,
"precision": "bf16",
"devices": [
0
],
"accelerator": "auto"
},
"qwen3_alignment": {
"enabled": true,
"embedding_path": "",
"projection_dim": 4096,
"temperature": 0.07,
"loss_weight": 0.1
},
"ntv3_embedding_path": "../../embeddings/reference_ntv3_embeddings.h5",
"data_path": "",
"output_dir": "./outputs",
"experiment_name": "MGM2-medium",
"seed": 42
}