End of training

README.md

@@ -1,54 +1,33 @@
 ---
 license: cc-by-nc-sa-4.0
+base_model: microsoft/layoutxlm-base
 tags:
 - generated_from_trainer
-base_model: microsoft/layoutxlm-base
 datasets:
-- nielsr/XFUN
-inference: false
+- xfun
 model-index:
 - name: layoutxlm-finetuned-xfund-fr
   results: []
 ---
 
-# layoutxlm-finetuned-xfund-fr
-
-This model is a fine-tuned version of [microsoft/layoutxlm-base](https://huggingface.co/microsoft/layoutxlm-base) on the [XFUND](https://github.com/doc-analysis/XFUND) dataset (French split).
-
-## Model usage
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
 
-Note that this model requires Tesseract, French package, in order to perform inference. You can install it using `!sudo apt-get install tesseract-ocr-fra`.
-
-Here's how to use this model:
-
-```
-from transformers import AutoProcessor, AutoModelForTokenClassification
-import torch
-from PIL import Image
-
-processor = AutoProcessor.from_pretrained("nielsr/layoutxlm-finetuned-xfund-fr")
-model = AutoModelForTokenClassification.from_pretrained(nielsr/layoutxlm-finetuned-xfund-fr")
+# layoutxlm-finetuned-xfund-fr
 
-# assuming you have a French document, turned into an image
-image = Image.open("...").convert("RGB")
+This model is a fine-tuned version of [microsoft/layoutxlm-base](https://huggingface.co/microsoft/layoutxlm-base) on the xfun dataset.
 
-# prepare for the model
-encoding = processor(image, padding="max_length", max_length=512, truncation=True, return_tensors="pt")
+## Model description
 
-with torch.no_grad():
-  outputs = model(**encoding)
-  logits = outputs.logits
-  
-predictions = logits.argmax(-1)
-```
+More information needed
 
 ## Intended uses & limitations
 
-This model can be used for NER on French scanned documents. It can recognize 4 categories: "question", "answer", "header" and "other".
+More information needed
 
 ## Training and evaluation data
 
-This checkpoint used the French portion of the multilingual [XFUND](https://github.com/doc-analysis/XFUND) dataset.
+More information needed
 
 ## Training procedure
 
@@ -70,7 +49,7 @@ The following hyperparameters were used during training:
 
 ### Framework versions
 
-- Transformers 4.22.1
-- Pytorch 1.10.0+cu111
-- Datasets 2.4.0
-- Tokenizers 0.12.1
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1