updated read me and json files.

README.md

@@ -3,19 +3,33 @@
 ## Overview
 This repository contains a fine-tuned version of the [CLIP ViT Base Patch32](https://huggingface.co/tanganke/clip-vit-base-patch32_pcam) model on the [PatchCamelyon (PCAM)](https://huggingface.co/datasets/1aurent/PatchCamelyon) dataset. The model is optimized for histopathological image classification.
 
-## Model Details
-- **Base Model**: CLIP ViT Base Patch32
-- **Dataset**: PatchCamelyon (PCAM)
-- **Optimizer**: AdamW
-- **Loss Function**: Cross-Entropy Loss
-- **Batch Size**: 32
-- **Hardware**: Trained on GPU
+---
+tags:
+- vision
+- clip
+- fine-tuned
+- PatchCamelyon
+- medical-imaging
+license: apache-2.0
+library_name: transformers
+model_type: clip_vision_model
+datasets:
+- 1aurent/PatchCamelyon
+---
 
-## Training Performance
-- **Epoch 1 Results:**
-  - **Train Loss**: 0.1520
+## Model Details
+- **Base Model**: `openai/clip-vit-base-patch32`
+- **Dataset**: `PatchCamelyon`
+- **Fine-tuned for**: Medical image classification (tumor vs. non-tumor)
+- **Evaluation Results**:
   - **Train Accuracy**: 94.35%
   - **Validation Accuracy**: 95.16%
+- **Hardware**: Trained on GPU-A100
+
+## Training Performance
+- **Train Loss**: 0.1520
+- **Train Accuracy**: 94.35%
+- **Validation Accuracy**: 95.16%
 
 ## Usage
 ### Installation

config.json

@@ -0,0 +1,20 @@
+{
+    "_name_or_path": "openai/clip-vit-base-patch32",
+    "architectures": ["CLIPVisionModel"],
+    "attention_dropout": 0.0,
+    "dropout": 0.0,
+    "hidden_act": "quick_gelu",
+    "hidden_size": 768,
+    "image_size": 224,
+    "initializer_factor": 1.0,
+    "initializer_range": 0.02,
+    "intermediate_size": 3072,
+    "layer_norm_eps": 1e-05,
+    "model_type": "clip_vision_model",
+    "num_attention_heads": 12,
+    "num_channels": 3,
+    "num_hidden_layers": 12,
+    "patch_size": 32,
+    "projection_dim": 512,
+    "torch_dtype": "float32"
+}