Update README.md

README.md

@@ -4,11 +4,11 @@ base_model: microsoft/swinv2-base-patch4-window12-192-22k
 tags:
 - generated_from_trainer
 datasets:
-- imagefolder
+- p1atdev/pvc
 metrics:
 - accuracy
 model-index:
-- name: pvc-quality-swinv2-base-2
+- name: pvc-quality-swinv2-base
   results:
   - task:
       name: Image Classification
@@ -23,14 +23,15 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.5317220543806647
+library_name: transformers
 ---
 
 <!-- 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. -->
 
-# pvc-quality-swinv2-base-2
+# pvc-quality-swinv2-base
 
-This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on the imagefolder dataset.
+This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on the [pvc figure images dataset](https://huggingface.co/datasets/p1atdev/pvc).
 It achieves the following results on the evaluation set:
 - Loss: 1.2396
 - Accuracy: 0.5317
@@ -84,4 +85,4 @@ The following hyperparameters were used during training:
 - Transformers 4.34.1
 - Pytorch 2.0.0+cu118
 - Datasets 2.14.5
-- Tokenizers 0.14.0
+- Tokenizers 0.14.0