Update README.md

README.md

@@ -5,71 +5,37 @@ tags:
 metrics:
 - rouge
 model-index:
-- name: DanSumT5-largeV_38143V_15157V_96478
+- name: DaMedSum-large
   results: []
+pipeline_tag: summarization
 ---
 
 <!-- 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. -->
 
-# DanSumT5-largeV_38143V_15157V_96478
-
-This model is a fine-tuned version of [emilstabil/DanSumT5-largeV_38143V_15157](https://huggingface.co/emilstabil/DanSumT5-largeV_38143V_15157) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.9819
-- Rouge1: 35.982
-- Rouge2: 12.5438
-- Rougel: 22.7137
-- Rougelsum: 33.5334
-- Gen Len: 124.173
+```
+ _____    ______   __    __   ______   _____    ______   __  __   __    __    
+/\  __-. /\  __ \ /\ "-./  \ /\  ___\ /\  __-. /\  ___\ /\ \/\ \ /\ "-./  \   
+\ \ \/\ \\ \  __ \\ \ \-./\ \\ \  __\ \ \ \/\ \\ \___  \\ \ \_\ \\ \ \-./\ \  
+ \ \____- \ \_\ \_\\ \_\ \ \_\\ \_____\\ \____- \/\_____\\ \_____\\ \_\ \ \_\ 
+  \/____/  \/_/\/_/ \/_/  \/_/ \/_____/ \/____/  \/_____/ \/_____/ \/_/  \/_/ 
+                                                                                                                                                                        
+```
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 4
-- eval_batch_size: 4
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 16
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 11
-
-### Training results
+This repository contains a model for Danish abstractive summarisation of medicaltext. 
 
-| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
-| No log        | 0.99  | 118  | 1.9875          | 35.6378 | 12.3785 | 22.4666 | 33.224    | 123.1814 |
-| No log        | 2.0   | 237  | 1.9991          | 35.9161 | 12.5761 | 22.7594 | 33.6048   | 123.5865 |
-| No log        | 3.0   | 356  | 1.9994          | 36.0651 | 12.7545 | 22.9642 | 33.6968   | 123.6203 |
-| No log        | 4.0   | 475  | 1.9980          | 35.9273 | 12.6691 | 22.818  | 33.609    | 123.4515 |
-| 1.4198        | 4.99  | 593  | 2.0076          | 35.5438 | 12.2242 | 22.5019 | 33.237    | 123.7257 |
-| 1.4198        | 6.0   | 712  | 2.0032          | 36.0019 | 12.7386 | 22.9014 | 33.7588   | 124.5443 |
-| 1.4198        | 7.0   | 831  | 2.0001          | 35.8585 | 12.7149 | 22.8298 | 33.6196   | 124.4008 |
-| 1.4198        | 8.0   | 950  | 1.9945          | 35.6975 | 12.4727 | 22.6524 | 33.3949   | 124.5316 |
-| 1.4397        | 8.99  | 1068 | 1.9898          | 35.944  | 12.6829 | 22.9022 | 33.5212   | 124.1181 |
-| 1.4397        | 10.0  | 1187 | 1.9843          | 36.0341 | 12.5681 | 22.7855 | 33.5415   | 124.0084 |
-| 1.4397        | 10.93 | 1298 | 1.9819          | 35.982  | 12.5438 | 22.7137 | 33.5334   | 124.173  |
+This model is a fine-tuned version of DanSum-large on a danish medical dataset.
 
+## Authors
+Nicolaj Larsen,
+Mikkel Kildeberg &
+Emil Schledermann
 
 ### Framework versions
 
 - Transformers 4.30.2
 - Pytorch 1.12.1+git7548e2f
 - Datasets 2.13.2
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3