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@@ -1,81 +1,81 @@
----
-tags:
-  - image-to-text
-  - image-captioning
-license: apache-2.0
-metrics:
-  - rouge
-datasets:
-  - nlphuji/flickr30k
-widget:
-  - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
-    example_title: Savanna
-  - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
-    example_title: Football Match
-  - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/airport.jpg
-    example_title: Airport
-base_model:
-  - google/vit-base-patch16-224-in21k
-
-model-index:
-  - name: mozilla/distilvit
-    results:
-      - task:
-          type: image-to-text
-          name: Image To Text
-        dataset:
-          name: nlphuji/flickr30k
-          type: nlphuji/flickr30k
-        metrics:
-          - name: ROUGE-1
-            type: rouge
-            value: 43.006
-            verified: true
-          - name: ROUGE-2
-            type: rouge
-            value: 16.9939
-            verified: true
-          - name: ROUGE-L
-            type: rouge
-            value: 38.8923
-            verified: true
-          - name: ROUGE-LSUM
-            type: rouge
-            value: 38.8877
-            verified: true
-          - name: loss
-            type: loss
-            value: 0.19939416646957397
-          - name: gen_len
-            type: gen_len
-            value: 11.327256736227712
-            verified: true
----
-
-# distilvit
-
-This model is a work in progress. Fine-tuned version of those base models:
-
-- a VIT model for the image encoder: https://huggingface.co/google/vit-base-patch16-224-in21k
-- a Distilled GPT-2 model for the text decoder: https://huggingface.co/distilbert/distilgpt2
-
-This model was trained on:
-
-- Flickr30k : https://huggingface.co/datasets/nlphuji/flickr30k
-- COCO 2017: https://cocodataset.org
-
-You can get that checkpoint using the 3083a3cef6e3c8dd90df3f088074bbe836b0f403 commit.
-
-It was then further fine-tuned on :
-
-- Flickr30k debiased: https://huggingface.co/datasets/Mozilla/flickr30k-transformed-captions
-- DocOrNot: https://huggingface.co/datasets/Mozilla/docornot
-
-You can find the code used to create the model here: https://github.com/mozilla/distilvit
-
-### Framework versions
-
-- Transformers 4.40.2
-- Pytorch 2.3.0+cu121
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+---
+tags:
+  - image-to-text
+  - image-captioning
+license: apache-2.0
+metrics:
+  - rouge
+datasets:
+  - nlphuji/flickr30k
+widget:
+  - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
+    example_title: Savanna
+  - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
+    example_title: Football Match
+  - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/airport.jpg
+    example_title: Airport
+base_model:
+  - google/vit-base-patch16-224-in21k
+
+model-index:
+  - name: mozilla/distilvit
+    results:
+      - task:
+          type: image-to-text
+          name: Image To Text
+        dataset:
+          name: nlphuji/flickr30k
+          type: nlphuji/flickr30k
+        metrics:
+          - name: ROUGE-1
+            type: rouge
+            value: 43.006
+            verified: true
+          - name: ROUGE-2
+            type: rouge
+            value: 16.9939
+            verified: true
+          - name: ROUGE-L
+            type: rouge
+            value: 38.8923
+            verified: true
+          - name: ROUGE-LSUM
+            type: rouge
+            value: 38.8877
+            verified: true
+          - name: loss
+            type: loss
+            value: 0.19939416646957397
+          - name: gen_len
+            type: gen_len
+            value: 11.327256736227712
+            verified: true
+---
+
+# distilvit
+
+This model is a work in progress. Fine-tuned version of those base models:
+
+- a VIT model for the image encoder: https://huggingface.co/google/vit-base-patch16-224-in21k
+- a Distilled GPT-2 model for the text decoder: https://huggingface.co/distilbert/distilgpt2
+
+This model was trained on:
+
+- Flickr30k : https://huggingface.co/datasets/nlphuji/flickr30k
+- COCO 2017: https://cocodataset.org
+
+You can get that checkpoint using the 3083a3cef6e3c8dd90df3f088074bbe836b0f403 commit.
+
+It was then further fine-tuned on :
+
+- Flickr30k debiased: https://huggingface.co/datasets/Mozilla/flickr30k-transformed-captions
+- DocOrNot: https://huggingface.co/datasets/Mozilla/docornot
+
+You can find the code used to create the model here: https://github.com/mozilla/distilvit
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1