Initial commit of the trained NER model with code

config.json

@@ -4,6 +4,10 @@
     "ExtendedMultitaskModelForTokenClassification"
   ],
   "attention_probs_dropout_prob": 0.1,
+  "auto_map": {
+    "AutoConfig": "configuration.ImpressoConfig",
+    "AutoModelForTokenClassification": "models.ExtendedMultitaskModelForTokenClassification"
+  },
   "classifier_dropout": null,
   "custom_pipelines": {
     "generic-ner": {

configuration.py

@@ -0,0 +1,45 @@
+from transformers import PretrainedConfig
+
+
+class ImpressoConfig(PretrainedConfig):
+    model_type = "extended_multitask"
+
+    def __init__(
+        self,
+        vocab_size=30522,
+        hidden_size=768,
+        num_hidden_layers=12,
+        num_attention_heads=12,
+        intermediate_size=3072,
+        hidden_act="gelu",
+        hidden_dropout_prob=0.1,
+        attention_probs_dropout_prob=0.1,
+        max_position_embeddings=512,
+        type_vocab_size=2,
+        initializer_range=0.02,
+        layer_norm_eps=1e-12,
+        pad_token_id=0,
+        position_embedding_type="absolute",
+        use_cache=True,
+        classifier_dropout=None,
+        pretrained_config=None,
+        **kwargs,
+    ):
+        super().__init__(pad_token_id=pad_token_id, **kwargs)
+
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.hidden_act = hidden_act
+        self.intermediate_size = intermediate_size
+        self.hidden_dropout_prob = hidden_dropout_prob
+        self.attention_probs_dropout_prob = attention_probs_dropout_prob
+        self.max_position_embeddings = max_position_embeddings
+        self.type_vocab_size = type_vocab_size
+        self.initializer_range = initializer_range
+        self.layer_norm_eps = layer_norm_eps
+        self.position_embedding_type = position_embedding_type
+        self.use_cache = use_cache
+        self.classifier_dropout = classifier_dropout
+        self.pretrained_config = pretrained_config