End of training

README.md

@@ -1,16 +1,97 @@
 ---
-license: apache-2.0
+tags:
+- generated_from_trainer
 datasets:
 - beans
 metrics:
 - accuracy
-library_name: transformers
-pipeline_tag: image-classification
+model-index:
+- name: resnet-mobilenet-beans
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: beans
+      type: beans
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7265625
 ---
-### ResNet Distilled to MobileNetv2
 
-This repository contains the MobileNetv2 model trained using distilling Resnet-50.
+<!-- 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. -->
 
-It is trained for educational purposes, on beans dataset. 🫘 
+# resnet-mobilenet-beans
 
-It contains TensorBoard logs from training (find it on the tab above 👆 ).
+This model is a fine-tuned version of [](https://huggingface.co/) on the beans dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5922
+- Accuracy: 0.7266
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 25
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9217        | 1.0   | 130  | 1.0079          | 0.3835   |
+| 0.8973        | 2.0   | 260  | 0.8349          | 0.4286   |
+| 0.7912        | 3.0   | 390  | 0.8905          | 0.5414   |
+| 0.7151        | 4.0   | 520  | 1.1400          | 0.4887   |
+| 0.6797        | 5.0   | 650  | 4.5343          | 0.4135   |
+| 0.6471        | 6.0   | 780  | 2.1551          | 0.3985   |
+| 0.5989        | 7.0   | 910  | 0.8552          | 0.6090   |
+| 0.6252        | 8.0   | 1040 | 1.7453          | 0.5489   |
+| 0.6025        | 9.0   | 1170 | 0.7852          | 0.6466   |
+| 0.5643        | 10.0  | 1300 | 1.4728          | 0.6090   |
+| 0.5505        | 11.0  | 1430 | 1.1570          | 0.6015   |
+| 0.5207        | 12.0  | 1560 | 3.2526          | 0.4436   |
+| 0.4957        | 13.0  | 1690 | 0.6617          | 0.6541   |
+| 0.4935        | 14.0  | 1820 | 0.7502          | 0.6241   |
+| 0.4836        | 15.0  | 1950 | 1.2039          | 0.5338   |
+| 0.4648        | 16.0  | 2080 | 1.0283          | 0.5338   |
+| 0.4662        | 17.0  | 2210 | 0.6695          | 0.7293   |
+| 0.4351        | 18.0  | 2340 | 0.8694          | 0.5940   |
+| 0.4286        | 19.0  | 2470 | 1.2751          | 0.4737   |
+| 0.4166        | 20.0  | 2600 | 0.8719          | 0.6241   |
+| 0.4263        | 21.0  | 2730 | 0.8767          | 0.6015   |
+| 0.4261        | 22.0  | 2860 | 1.2780          | 0.5564   |
+| 0.4124        | 23.0  | 2990 | 1.4095          | 0.5940   |
+| 0.4082        | 24.0  | 3120 | 0.9104          | 0.6015   |
+| 0.3923        | 25.0  | 3250 | 0.6430          | 0.7068   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

pytorch_model.bin

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