End of training

README.md

@@ -5,9 +5,24 @@ tags:
 - generated_from_trainer
 datasets:
 - imagefolder
+metrics:
+- accuracy
 model-index:
 - name: msi-resnet-18-pretrain
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8675487465181059
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,13 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.4090
-- eval_accuracy: 0.8648
-- eval_runtime: 45.6695
-- eval_samples_per_second: 157.216
-- eval_steps_per_second: 9.831
-- epoch: 2.0
-- step: 3125
+- Loss: 0.4121
+- Accuracy: 0.8675
 
 ## Model description
 
@@ -51,7 +61,16 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 10
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1724        | 1.0   | 1562 | 0.3597          | 0.8806   |
+| 0.0543        | 2.0   | 3125 | 0.3707          | 0.8875   |
+| 0.0834        | 3.0   | 4686 | 0.4121          | 0.8675   |
+
 
 ### Framework versions
 

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:f846819b6d30be6b510dbda3e42b31cb291224b57f2d12fae6135e6a8d830ca6
 size 44778700