End of training

README.md

@@ -1,12 +1,28 @@
 ---
 library_name: transformers
+base_model: MoGHenry/cat_dog_classifier_with_small_datasest
 tags:
 - generated_from_trainer
 datasets:
 - imagefolder
+metrics:
+- accuracy
 model-index:
 - name: cat_dog_classifier_with_small_datasest
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9571428571428572
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -14,15 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # cat_dog_classifier_with_small_datasest
 
-This model was trained from scratch on the imagefolder dataset.
+This model is a fine-tuned version of [MoGHenry/cat_dog_classifier_with_small_datasest](https://huggingface.co/MoGHenry/cat_dog_classifier_with_small_datasest) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.2202
-- eval_model_preparation_time: 0.0044
-- eval_accuracy: 0.9286
-- eval_runtime: 2.4201
-- eval_samples_per_second: 57.849
-- eval_steps_per_second: 7.438
-- step: 0
+- Loss: 0.1495
+- Accuracy: 0.9571
 
 ## Model description
 
@@ -42,13 +53,29 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 4
+- train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- num_epochs: 20
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 18   | 0.1574          | 0.9571   |
+| No log        | 2.0   | 36   | 0.1638          | 0.9429   |
+| No log        | 3.0   | 54   | 0.1581          | 0.9429   |
+| No log        | 4.0   | 72   | 0.1470          | 0.9571   |
+| No log        | 5.0   | 90   | 0.1424          | 0.9571   |
+| No log        | 6.0   | 108  | 0.1389          | 0.9643   |
+| No log        | 7.0   | 126  | 0.1632          | 0.9429   |
+| No log        | 8.0   | 144  | 0.1510          | 0.95     |
+| No log        | 9.0   | 162  | 0.1474          | 0.95     |
+| No log        | 10.0  | 180  | 0.1430          | 0.9571   |
+
 
 ### Framework versions
 

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "/kaggle/working/cat_dog_classifier_with_small_datasest/checkpoint-90",
+  "_name_or_path": "MoGHenry/cat_dog_classifier_with_small_datasest",
   "architectures": [
     "ResNetForImageClassification"
   ],

model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:04949232c69770d3b7d2032a7b69d4adbcebe5123744e801f347ae7e4717f930
 size 94302952

training_args.bin

@@ -1,3 +1,3 @@
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+oid sha256:47e95f353aa382ffd13dcb9ba4245538c32f73247163399a2ff7073b46bcb566
 size 5368