Model save

README.md

@@ -0,0 +1,87 @@
+---
+license: apache-2.0
+base_model: xiaopch/vit-base-patch16-224-finetuned
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-base-patch16-224-finetuned-for-agricultural
+  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: 0.7289156626506024
+---
+
+<!-- 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. -->
+
+# vit-base-patch16-224-finetuned-for-agricultural
+
+This model is a fine-tuned version of [xiaopch/vit-base-patch16-224-finetuned](https://huggingface.co/xiaopch/vit-base-patch16-224-finetuned) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9039
+- Accuracy: 0.7289
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9131        | 1.0   | 35   | 1.0878          | 0.6847   |
+| 0.8066        | 2.0   | 70   | 0.9933          | 0.7189   |
+| 0.7259        | 3.0   | 105  | 0.9445          | 0.7249   |
+| 0.6719        | 4.0   | 140  | 0.9246          | 0.7309   |
+| 0.6056        | 5.0   | 175  | 0.9258          | 0.7229   |
+| 0.5576        | 6.0   | 210  | 0.9230          | 0.7309   |
+| 0.5113        | 7.0   | 245  | 0.9152          | 0.7169   |
+| 0.488         | 8.0   | 280  | 0.9119          | 0.7209   |
+| 0.4822        | 9.0   | 315  | 0.9061          | 0.7269   |
+| 0.4163        | 10.0  | 350  | 0.9039          | 0.7289   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cbd429339180f1ff06845f578c7c7e3e15373c2c5a6fd639e5bd3b11eab32c0d
+oid sha256:30645b921a30a921cc4ab3dd187aa5018b48db68245a3ab007f1a8dd20bcbba5
 size 343270116

runs/Nov30_14-15-54_4b23d0e9dade/events.out.tfevents.1701353778.4b23d0e9dade.2219.2

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d2e63f20b9b8dbe54a8c7efd141f0f5fde107b04913e804116bb39d7510ca81b
-size 13876
+oid sha256:78a968ba65da41e60538aa3f1916fdee05190ef724062f99a89902eaf913036a
+size 14230