add model

README.md

@@ -2,24 +2,26 @@
 tags:
 - generated_from_trainer
 datasets:
-- setimes
+- wikiann
 metrics:
 - precision
 - recall
 - f1
 - accuracy
-language:
-- sr
 model_index:
 - name: distilbert-srb-ner
   results:
   - task:
       name: Token Classification
       type: token-classification
+    dataset:
+      name: wikiann
+      type: wikiann
+      args: sr
     metric:
       name: Accuracy
       type: accuracy
-      value: 0.966779551685212
+      value: 0.9570619691726958
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -27,40 +29,25 @@ should probably proofread and complete it, then remove this comment. -->
 
 # distilbert-srb-ner
 
-This model was finetuned from Aleksandar/distilbert-srb-cased-oscar on the setimes.SR dataset.
-
+This model was trained from scratch on the wikiann dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1531
-- Precision: 0.8296
-- Recall: 0.8593
-- F1: 0.8442
-- Accuracy: 0.9668
+- Loss: 0.2532
+- Precision: 0.8859
+- Recall: 0.9066
+- F1: 0.8962
+- Accuracy: 0.9571
 
 ## Model description
 
-Finetuned model of Aleksandar/distilbert-srb-cased-oscar on settimes.SR dataset
+More information needed
 
 ## Intended uses & limitations
 
-| Tag (IOB)   | Numerical representation | Meaning   (Beginning = B.,  Inside = I.) |
-|-------------|--------------------------|------------------------------------------|
-| O           | 0                        | Other                                    |
-| B-per       | 1                        | B.Person                                 |
-| I-per       | 2                        | I. Person                                |
-| B-org       | 3                        | B. organization                          |
-| I-org       | 4                        | I. organization                          |
-| B-loc       | 5                        | B. location                              |
-| I-loc       | 6                        | I. location                              |
-| B-misc      | 7                        | B. Miscellaneous                         |
-| I-misc      | 8                        | I. Miscellaneous                         |
-| B-deriv-per | 9                        | B. Derived Person                        |
-
-MIT license
+More information needed
 
 ## Training and evaluation data
 
-Training was performed with seqeval as the evaluation metric.  
-0.15% of dataset (setimes.SR) was used as validation dataset. 
+More information needed
 
 ## Training procedure
 
@@ -77,18 +64,18 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 207  | 0.2235          | 0.7038    | 0.7314 | 0.7174 | 0.9381   |
-| No log        | 2.0   | 414  | 0.1538          | 0.7565    | 0.7937 | 0.7746 | 0.9548   |
-| 0.2327        | 3.0   | 621  | 0.1467          | 0.7863    | 0.8171 | 0.8014 | 0.9594   |
-| 0.2327        | 4.0   | 828  | 0.1398          | 0.8009    | 0.8526 | 0.8260 | 0.9630   |
-| 0.0771        | 5.0   | 1035 | 0.1319          | 0.8021    | 0.8376 | 0.8195 | 0.9637   |
-| 0.0771        | 6.0   | 1242 | 0.1482          | 0.8098    | 0.8513 | 0.8300 | 0.9652   |
-| 0.0771        | 7.0   | 1449 | 0.1454          | 0.8234    | 0.8510 | 0.8370 | 0.9667   |
-| 0.0339        | 8.0   | 1656 | 0.1503          | 0.8310    | 0.8547 | 0.8427 | 0.9663   |
-| 0.0339        | 9.0   | 1863 | 0.1525          | 0.8279    | 0.8587 | 0.8430 | 0.9661   |
-| 0.0169        | 10.0  | 2070 | 0.1531          | 0.8296    | 0.8593 | 0.8442 | 0.9668   |
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2615        | 1.0   | 1250  | 0.2126          | 0.8268    | 0.8327 | 0.8297 | 0.9319   |
+| 0.1568        | 2.0   | 2500  | 0.1775          | 0.8695    | 0.8699 | 0.8697 | 0.9472   |
+| 0.1017        | 3.0   | 3750  | 0.1718          | 0.8649    | 0.8857 | 0.8752 | 0.9504   |
+| 0.066         | 4.0   | 5000  | 0.1906          | 0.8734    | 0.8930 | 0.8831 | 0.9530   |
+| 0.0413        | 5.0   | 6250  | 0.2076          | 0.8805    | 0.8992 | 0.8897 | 0.9549   |
+| 0.03          | 6.0   | 7500  | 0.2257          | 0.8758    | 0.9045 | 0.8899 | 0.9554   |
+| 0.0213        | 7.0   | 8750  | 0.2286          | 0.8864    | 0.9015 | 0.8939 | 0.9556   |
+| 0.0157        | 8.0   | 10000 | 0.2454          | 0.8874    | 0.9021 | 0.8947 | 0.9566   |
+| 0.01          | 9.0   | 11250 | 0.2486          | 0.8878    | 0.9043 | 0.8960 | 0.9573   |
+| 0.0076        | 10.0  | 12500 | 0.2532          | 0.8859    | 0.9066 | 0.8962 | 0.9571   |
 
 
 ### Framework versions

config.json

@@ -15,10 +15,7 @@
     "3": "LABEL_3",
     "4": "LABEL_4",
     "5": "LABEL_5",
-    "6": "LABEL_6",
-    "7": "LABEL_7",
-    "8": "LABEL_8",
-    "9": "LABEL_9"
+    "6": "LABEL_6"
   },
   "initializer_range": 0.02,
   "label2id": {
@@ -28,10 +25,7 @@
     "LABEL_3": 3,
     "LABEL_4": 4,
     "LABEL_5": 5,
-    "LABEL_6": 6,
-    "LABEL_7": 7,
-    "LABEL_8": 8,
-    "LABEL_9": 9
+    "LABEL_6": 6
   },
   "max_position_embeddings": 512,
   "model_type": "distilbert",

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:ec278e2e6a712f0e95da93b29462d1a5264e4ece5970fd9a42654c335808a512
+size 326138357

training_args.bin

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 size 2671