Training in progress, epoch 0

README.md

@@ -1,7 +1,7 @@
 ---
 library_name: transformers
 license: apache-2.0
-base_model: microsoft/resnet-50
+base_model: CGCTG/orientation_resnet-50
 tags:
 - generated_from_trainer
 datasets:
@@ -9,7 +9,7 @@ datasets:
 metrics:
 - accuracy
 model-index:
-- name: model
+- name: model_resnet-50
   results:
   - task:
       name: Image Classification
@@ -23,18 +23,18 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5340086830680174
+      value: 0.48552821997105644
 ---
 
 <!-- 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. -->
 
-# model
+# model_resnet-50
 
-This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
+This model is a fine-tuned version of [CGCTG/orientation_resnet-50](https://huggingface.co/CGCTG/orientation_resnet-50) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7631
-- Accuracy: 0.5340
+- Loss: 0.8638
+- Accuracy: 0.4855
 
 ## Model description
 
@@ -69,7 +69,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.8153        | 0.9942 | 86   | 0.7631          | 0.5340   |
+| 0.8151        | 0.9942 | 86   | 0.8638          | 0.4855   |
 
 
 ### Framework versions

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "microsoft/resnet-50",
+  "_name_or_path": "CGCTG/orientation_resnet-50",
   "architectures": [
     "ResNetForImageClassification"
   ],

model.safetensors

@@ -1,3 +1,3 @@
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 size 94319344

training_args.bin

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+size 5368