Create README.md

README.md

@@ -0,0 +1,33 @@
+---
+language: sq
+widget:
+- text: "Varianti AY.4.2 është më i lehtë për t'u transmetuar, thotë Francois Balu, drejtor i Institutit të Gjenetikës në Londër."
+---
+# Albanian Named Entity Recognition (NER) Model
+This model is the fine-tuned model of "bert-base-multilingual-cased" 
+using the famous WikiANN dataset presented
+in the "Cross-lingual Name Tagging and Linking for 282 Languages" [paper](https://aclanthology.org/P17-1178.pdf).
+# Fine-tuning parameters:
+```
+task = "ner"
+model_checkpoint = "bert-base-multilingual-cased"
+batch_size = 8 
+label_list = ['O', 'B-PER', 'I-PER', 'B-ORG', 'I-ORG', 'B-LOC', 'I-LOC']
+max_length = 512 
+learning_rate = 2e-5 
+num_train_epochs = 3 
+weight_decay = 0.01 
+```
+# How to use: 
+```
+model = AutoModelForTokenClassification.from_pretrained("akdeniz27/mbert-base-albanian-cased-ner")
+tokenizer = AutoTokenizer.from_pretrained("akdeniz27/mbert-base-albanian-cased-ner")
+ner = pipeline('ner', model=model, tokenizer=tokenizer, aggregation_strategy="first")
+ner("<your text here>")
+```
+Pls refer "https://huggingface.co/transformers/_modules/transformers/pipelines/token_classification.html" for entity grouping with aggregation_strategy parameter.
+# Reference test results:
+* accuracy: 0.9719268816143276
+* f1: 0.9192366826444787
+* precision: 0.9171629669734704
+* recall: 0.9213197969543148