Model save

README.md

@@ -0,0 +1,96 @@
+---
+base_model: openai/clip-vit-base-patch32
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: ktp-crop-clip
+  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: 0.9864864864864865
+---
+
+<!-- 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. -->
+
+# ktp-crop-clip
+
+This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1223
+- Accuracy: 0.9865
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.96  | 6    | 0.8954          | 0.5270   |
+| 0.7112        | 1.92  | 12   | 0.6729          | 0.5405   |
+| 0.7112        | 2.88  | 18   | 0.6407          | 0.7297   |
+| 0.4413        | 4.0   | 25   | 0.1279          | 0.9459   |
+| 0.0935        | 4.96  | 31   | 0.1436          | 0.9730   |
+| 0.0935        | 5.92  | 37   | 0.0021          | 1.0      |
+| 0.0697        | 6.88  | 43   | 0.2862          | 0.9459   |
+| 0.161         | 8.0   | 50   | 0.0843          | 0.9595   |
+| 0.161         | 8.96  | 56   | 0.2255          | 0.9459   |
+| 0.0061        | 9.92  | 62   | 0.4678          | 0.9054   |
+| 0.0061        | 10.88 | 68   | 0.3299          | 0.9189   |
+| 0.0309        | 12.0  | 75   | 0.5189          | 0.9189   |
+| 0.0025        | 12.96 | 81   | 0.0850          | 0.9865   |
+| 0.0025        | 13.92 | 87   | 0.0720          | 0.9865   |
+| 0.0042        | 14.88 | 93   | 0.0745          | 0.9865   |
+| 0.0002        | 16.0  | 100  | 0.0869          | 0.9865   |
+| 0.0002        | 16.96 | 106  | 0.0895          | 0.9865   |
+| 0.0001        | 17.92 | 112  | 0.1127          | 0.9865   |
+| 0.0001        | 18.88 | 118  | 0.1219          | 0.9865   |
+| 0.0           | 19.2  | 120  | 0.1223          | 0.9865   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:766c8f07618f6042af8b1083cbb05a35e0f6d7f5429ec68dcfc5e58789f1f2cb
+oid sha256:aee1030481d1f60449a2e5e484ff6178f7b619c02597b243357a5b3eef02fd5f
 size 349854120

runs/Jul03_08-10-40_199eb666e01e/events.out.tfevents.1719994251.199eb666e01e.34.4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8877714b100a1994c1cdef76120b650df3f3c6ed7a5e73375ed58a94d87b1fe0
-size 13026
+oid sha256:cca1e6b0da2d601e556924bc4efaed20b11a13e55bfeecacadfdfed3958a4683
+size 13898