Model save

README.md

@@ -0,0 +1,87 @@
+---
+license: apache-2.0
+base_model: google/vit-hybrid-base-bit-384
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: hybrid-cnn-vit
+  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: 0.8707767328456983
+---
+
+<!-- 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. -->
+
+# hybrid-cnn-vit
+
+This model is a fine-tuned version of [google/vit-hybrid-base-bit-384](https://huggingface.co/google/vit-hybrid-base-bit-384) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3384
+- Accuracy: 0.8708
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5277        | 1.0   | 202  | 0.3903          | 0.8210   |
+| 0.4623        | 2.0   | 404  | 0.3478          | 0.8415   |
+| 0.4497        | 3.0   | 606  | 0.3334          | 0.8520   |
+| 0.4074        | 4.0   | 808  | 0.3397          | 0.8460   |
+| 0.3552        | 5.0   | 1010 | 0.3227          | 0.8624   |
+| 0.3637        | 6.0   | 1212 | 0.3230          | 0.8617   |
+| 0.3316        | 7.0   | 1414 | 0.3189          | 0.8673   |
+| 0.31          | 8.0   | 1616 | 0.3804          | 0.8492   |
+| 0.2324        | 9.0   | 1818 | 0.3382          | 0.8662   |
+| 0.234         | 10.0  | 2020 | 0.3384          | 0.8708   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

runs/Mar17_08-37-46_4a576a550605/events.out.tfevents.1710664684.4a576a550605.2555.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5270f23d296bab8436715e31bcce97433d06d9b9bc87a6f53283e3088c798946
-size 50944
+oid sha256:129ac141d0a8dbdddacb7793c319648050ec5113d55b710ee274474aa97f9ad7
+size 51298