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README.md

@@ -5,41 +5,13 @@ multilinguality:
 - monolingual
 task_categories:
 - token-classification
-dataset_info:
-  features:
-  - name: tokens
-    sequence: string
-  - name: ner_tags_niv1
-    sequence: string
-  - name: ner_tags_niv2
-    sequence: string
-  - name: input_ids
-    sequence: int32
-  - name: attention_mask
-    sequence: int8
-  - name: labels_niv1
-    sequence: int64
-  - name: labels_niv2
-    sequence: int64
-  splits:
-  - name: train
-    num_bytes: 4985685
-    num_examples: 6084
-  - name: dev
-    num_bytes: 545374
-    num_examples: 676
-  - name: test
-    num_bytes: 1335125
-    num_examples: 1685
-  download_size: 1015644
-  dataset_size: 6866184
 ---
 
 # m1_fine_tuning_ocr_cmbert_iob2
 
 ## Introduction
 
-This dataset was used to perform **qualitative analysis** of [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) on **nested NER task** using Independant NER layers approach [M1]. 
+This dataset was used to fine-tuned [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) for **nested NER task** using Independant NER layers approach [M1]. 
 It contains Paris trade directories entries from the 19th century.
 
 ## Dataset parameters
@@ -76,4 +48,4 @@ FT |2|Geographical feature
 ```python
 from datasets import load_dataset
 
-train_dev_test = load_dataset("nlpso/m1_fine_tuning_ocr_cmbert_iob2")
+train_dev_test = load_dataset("nlpso/m1_fine_tuning_ocr_cmbert_iob2")