alter_config.json

{
  "model_type": "ConcatModelWithRationale",
  "hatebert_model": "GroNLP/HateBERT",
  "rationale_model": "bert-base-uncased",

  "training_config": {
    "cnn_filters": 128,
    "cnn_kernels": [2, 3, 4],
    "cnn_dropout": 0.3,
    "adapter_dim": 128,
    "max_length": 128,
    "num_labels": 2,

    "batch_size": 8,
    "learning_rate": 2e-5,
    "weight_decay": 0.05,
    "best_val_f1": 0.00
  },

  "architecture": {
    "temporal_cnn": "TemporalCNN (max+mean pooling)",
    "msa_cnn": "MultiScaleAttentionCNN (token attention pooling)",
    "selector": "Gumbel-Sigmoid Token Selector",
    "projection": "ProjectionMLP (concat CLS + CNN + rationale pooled)"
  },

  "notes": {
    "trained_with": "ConcatModelWithRationale",
    "framework": "PyTorch + Transformers",
    "encoder_main": "HateBERT",
    "encoder_rationale": "BERT-base-uncased"
  }
}