Upload folder using huggingface_hub

README.md

@@ -0,0 +1,39 @@
+---
+license: apache-2.0
+tags:
+- vision
+- image-classification
+datasets:
+- AI-Lab-Makerere/beans
+metrics:
+- accuracy
+model-index:
+- name: vit-beans-finetuned
+  results:
+  - task:
+      type: image-classification
+      name: Image Classification
+    dataset:
+      name: Beans
+      type: AI-Lab-Makerere/beans
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.95
+---
+# vit-beans-finetuned
+
+Fine-tuned ViT-Base on the Beans dataset.
+
+## Usage
+
+```python
+from transformers import pipeline
+clf = pipeline('image-classification', model='PR0G3T/vit-beans-finetuned')
+```
+
+## Training
+Trained for 1 epoch, batch 16, lr 5e-5, optimizer AdamW.
+
+## Limitations
+Model specific to bean-leaf images.

config.json

@@ -0,0 +1,35 @@
+{
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "angular_leaf_spot",
+    "1": "bean_rust",
+    "2": "healthy"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "angular_leaf_spot": 0,
+    "bean_rust": 1,
+    "healthy": 2
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "pooler_act": "tanh",
+  "pooler_output_size": 768,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.52.3"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:93dfeae1abf070af4b83db9a708fbe543a112ffcf6e868ae0908141a6d3fd995
+size 343227052

preprocessor_config.json

@@ -0,0 +1,23 @@
+{
+  "do_convert_rgb": null,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}