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README.md

@@ -1,3 +1,4 @@
+
 ---
 license: apache-2.0
 library_name: span-marker
@@ -7,15 +8,11 @@ tags:
 - ner
 - named-entity-recognition
 pipeline_tag: token-classification
-datasets:
-- DFKI-SLT/few-nerd
-language:
-- en
 ---
 
 # SpanMarker for Named Entity Recognition
 
-This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses [roberta-large](https://huggingface.co/roberta-large) as the underlying encoder.
+This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that can be usedfor Named Entity Recognition. In particular, this SpanMarker model uses [roberta-large](https://huggingface.co/roberta-large) as the underlying encoder. 
 
 ## Usage
 
@@ -25,15 +22,15 @@ To use this model for inference, first install the `span_marker` library:
 pip install span_marker
 ```
 
-You can then run inference as follows:
+You can then run inference with this model like so:
 
 ```python
 from span_marker import SpanMarkerModel
 
-# Download from Hub and run inference
-model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-roberta-large-fewnerd-fine-super")
+# Download from the 🤗 Hub
+model = SpanMarkerModel.from_pretrained("span_marker_model_name")
 # Run inference
 entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.")
 ```
 
-See the [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) repository for documentation and additional information on this model framework.
+See the [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) repository for documentation and additional information on this library.

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "models\\rl-full-5e-5-rl-1\\checkpoint-final",
+  "_name_or_path": "models\\rl-full-pl-marker-2\\checkpoint-final",
   "architectures": [
     "SpanMarkerModel"
   ],
@@ -32,6 +32,14 @@
     "id2label": {
       "0": "O",
       "1": "art-broadcastprogram",
+      "2": "art-film",
+      "3": "art-music",
+      "4": "art-other",
+      "5": "art-painting",
+      "6": "art-writtenart",
+      "7": "building-airport",
+      "8": "building-hospital",
+      "9": "building-hotel",
       "10": "building-library",
       "11": "building-other",
       "12": "building-restaurant",
@@ -42,7 +50,6 @@
       "17": "event-election",
       "18": "event-other",
       "19": "event-protest",
-      "2": "art-film",
       "20": "event-sportsevent",
       "21": "location-GPE",
       "22": "location-bodiesofwater",
@@ -53,7 +60,6 @@
       "27": "location-road/railway/highway/transit",
       "28": "organization-company",
       "29": "organization-education",
-      "3": "art-music",
       "30": "organization-government/governmentagency",
       "31": "organization-media/newspaper",
       "32": "organization-other",
@@ -64,7 +70,6 @@
       "37": "organization-sportsteam",
       "38": "other-astronomything",
       "39": "other-award",
-      "4": "art-other",
       "40": "other-biologything",
       "41": "other-chemicalthing",
       "42": "other-currency",
@@ -75,7 +80,6 @@
       "47": "other-law",
       "48": "other-livingthing",
       "49": "other-medical",
-      "5": "art-painting",
       "50": "person-actor",
       "51": "person-artist/author",
       "52": "person-athlete",
@@ -86,17 +90,13 @@
       "57": "person-soldier",
       "58": "product-airplane",
       "59": "product-car",
-      "6": "art-writtenart",
       "60": "product-food",
       "61": "product-game",
       "62": "product-other",
       "63": "product-ship",
       "64": "product-software",
       "65": "product-train",
-      "66": "product-weapon",
-      "7": "building-airport",
-      "8": "building-hospital",
-      "9": "building-hotel"
+      "66": "product-weapon"
     },
     "initializer_range": 0.02,
     "intermediate_size": 4096,
@@ -214,12 +214,12 @@
     "use_cache": true,
     "vocab_size": 50267
   },
-  "entity_max_length": 16,
-  "marker_max_length": 256,
-  "model_max_length": 512,
+  "entity_max_length": 8,
+  "marker_max_length": 128,
+  "model_max_length": 256,
   "model_max_length_default": 512,
   "model_type": "span-marker",
-  "outside_id": 0,
+  "span_marker_version": "1.0.0.dev",
   "torch_dtype": "float32",
   "transformers_version": "4.27.2",
   "vocab_size": 50267

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:888208234cecfb97b580e7b8267712b421a49840220cbd9f84ae279f2d4af0f3
+oid sha256:4d8bf73b0c3a973f9edadde6a620b247465b8ae0a24072daf1461a38ebe71103
 size 1422130805

tokenizer.json

@@ -1,21 +1,7 @@
 {
   "version": "1.0",
-  "truncation": {
-    "direction": "Right",
-    "max_length": 512,
-    "strategy": "LongestFirst",
-    "stride": 0
-  },
-  "padding": {
-    "strategy": {
-      "Fixed": 512
-    },
-    "direction": "Right",
-    "pad_to_multiple_of": null,
-    "pad_id": 1,
-    "pad_type_id": 0,
-    "pad_token": "<pad>"
-  },
+  "truncation": null,
+  "padding": null,
   "added_tokens": [
     {
       "id": 0,