HAV precision-optimised classifier v1

README.md

@@ -1,3 +1,58 @@
+base_model: "answerdotai/ModernBERT-base"
 ---
-license: mit
----
+# HAV classifier (modernbert-base)
+Binary: High Analytical Value (HAV) vs Low (LAV) for social posts. Precision-optimised (F0.5).
+
+## Data preparation
+Model has been trained on data with spam removed, spam posts could be classified as HAV. Not trained on tiktok data.
+
+## Operating point
+Apply a **decision threshold of 0.909** on `softmax(logits)[:, 1]`.
+Do NOT use argmax@0.5 — this model is precision-tuned and 0.5 gives far lower precision.
+
+## Metrics
+  "objective": {
+    "metric": "F0.5 (HAV)",
+    "beta": 0.5,
+    "min_hav_recall": 0.3,
+    "decision_threshold": 0.9099,
+    "val_selection": {
+      "threshold": 0.9099,
+      "hav_precision": 0.8238,
+      "hav_recall": 0.5035,
+      "nonhav_recall": 0.9753,
+      "fbeta": 0.7308,
+      "beta": 0.5
+    }
+  },
+  "data": {
+    "train_rows": 10866,
+    "train_hav": 2033,
+    "eval_rows": 2366,
+    "eval_hav": 440
+  },
+  "test_overall": {
+    "accuracy": 0.8762,
+    "hav_f05": 0.6841,
+    "hav_f1": 0.5936,
+    "macro_f1": 0.7603,
+    "weighted_f1": 0.865,
+    "average_precision": 0.7163
+  },
+  "test_per_class": {
+    "non_HAV": {
+      "precision": 0.8916,
+      "recall": 0.9652,
+      "f1-score": 0.927,
+      "support": 1926.0
+    },
+    "HAV": {
+      "precision": 0.7616,
+      "recall": 0.4864,
+      "f1-score": 0.5936,
+      "support": 440.0
+    }
+  }
+
+## Caveats
+Misclassfied negative class still an issue. pos_weight=4.9, max_length=256.

config.json

@@ -0,0 +1,86 @@
+{
+  "architectures": [
+    "ModernBertForSequenceClassification"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 50281,
+  "classifier_activation": "gelu",
+  "classifier_bias": false,
+  "classifier_dropout": 0.2,
+  "classifier_pooling": "mean",
+  "cls_token_id": 50281,
+  "decoder_bias": true,
+  "deterministic_flash_attn": false,
+  "dtype": "float32",
+  "embedding_dropout": 0.0,
+  "eos_token_id": 50282,
+  "global_attn_every_n_layers": 3,
+  "gradient_checkpointing": false,
+  "hav_decision_threshold": 0.9099,
+  "hidden_activation": "gelu",
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LAV",
+    "1": "HAV"
+  },
+  "initializer_cutoff_factor": 2.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 1152,
+  "label2id": {
+    "HAV": 1,
+    "LAV": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "layer_types": [
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention"
+  ],
+  "local_attention": 128,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "mlp_dropout": 0.0,
+  "model_type": "modernbert",
+  "norm_bias": false,
+  "norm_eps": 1e-05,
+  "num_attention_heads": 12,
+  "num_hidden_layers": 22,
+  "pad_token_id": 50283,
+  "position_embedding_type": "absolute",
+  "rope_parameters": {
+    "full_attention": {
+      "rope_theta": 160000.0,
+      "rope_type": "default"
+    },
+    "sliding_attention": {
+      "rope_theta": 10000.0,
+      "rope_type": "default"
+    }
+  },
+  "sep_token_id": 50282,
+  "sparse_pred_ignore_index": -100,
+  "sparse_prediction": false,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.13.1",
+  "vocab_size": 50368
+}

model.safetensors

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+size 598439784

tokenizer_config.json

@@ -0,0 +1,21 @@
+{
+  "backend": "tokenizers",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "is_local": true,
+  "local_files_only": false,
+  "mask_token": "[MASK]",
+  "max_length": 256,
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 8192,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "tokenizer_class": "TokenizersBackend",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

training_args.bin

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