Training in progress, epoch 1

README.md

@@ -1,6 +1,10 @@
 ---
 license: mit
 base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+datasets:
+- id_nergrit_corpus
 metrics:
 - precision
 - recall
@@ -31,38 +35,6 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.9850887866850908
-widget:
-- text: >-
-    Kebakaran hutan dan lahan terus terjadi dan semakin meluas di Kota
-    Palangkaraya, Kalimantan Tengah (Kalteng) pada Senin, 15 Nopember 2023 16.00
-    WIB. Bahkan kobaran api mulai membakar pondok warga dan mendekati
-    permukiman. BZK #RCTINews #SeputariNews #News #Karhutla #KebakaranHutan
-    #HutanKalimantan #SILVANUS_Italian_Pilot_Testing
-  example_title: Indonesia
-- text: >-
-    Wildfire rages for a second day in Evia destroying a Natura 2000 protected
-    pine forest. #wildfire #Evia #Natura2000 #Greece - 5:51 PM Aug 14, 2019
-  example_title: English
-- text: >-
-    Los incendios forestales obligaron a la evacuación de hasta 850 personas
-    cerca de la localidad valenciana de Montichelvo. - 21:57 3 de noviembre de
-    2023
-  example_title: Spanish
-- text: >-
-    Incendi boschivi nell'est del Paese: 2 persone uccise e più di 50 case
-    distrutte nello stato del Queensland. - 17.23 31 ottobre 2023
-  example_title: Italian
-- text: >-
-    Lesné požiare na Sicílii si vyžiadali dva ľudské životy a evakuáciu hotela
-    http://dlvr.it/SwW3sC - 20:57 23. september 2023
-  example_title: Slovak
-language:
-- id
-- en
-- es
-- it
-- sk
-pipeline_tag: token-classification
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -70,7 +42,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # xlm-roberta-base-ner-silvanus
 
-This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on named entity recognition.
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the id_nergrit_corpus dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.0635
 - Precision: 0.9186
@@ -117,4 +89,4 @@ The following hyperparameters were used during training:
 - Transformers 4.35.0
 - Pytorch 2.1.0+cu118
 - Datasets 2.14.6
-- Tokenizers 0.14.1
+- Tokenizers 0.14.1

model.safetensors

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runs/Nov14_23-33-01_server-cvis/events.out.tfevents.1700004806.server-cvis.816047.0

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tokenizer.json

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training_args.bin

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