sanali209/reitBF

README.md

@@ -1,31 +1,61 @@
 ---
+library_name: transformers
 tags:
-- image-classification
-- pytorch
-- huggingpics
-metrics:
-- accuracy
-
+- generated_from_trainer
+datasets:
+- imagefolder
 model-index:
-- name: sanali209/reitBF
-  results:
-  - task:
-      name: Image Classification
-      type: image-classification
-    metrics:
-      - name: Accuracy
-        type: accuracy
-        value: 0.8446534276008606
+- name: reitBF
+  results: []
 ---
 
-# sanali209/reitBF
+<!-- 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. -->
+
+# reitBF
+
+This model was trained from scratch on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0813
+
+## 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: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
 
-Autogenerated by HuggingPics🤗🖼️
+### Training results
 
-Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| No log        | 1.0   | 47   | 1.3983          |
+| No log        | 2.0   | 94   | 1.1390          |
+| No log        | 3.0   | 141  | 1.0888          |
+| No log        | 4.0   | 188  | 1.0813          |
 
-Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
 
+### Framework versions
 
-## Example Images
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

config.json

@@ -17,9 +17,9 @@
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "high": "0",
-    "low": "1",
-    "normal": "2"
+    "high": 0,
+    "low": 1,
+    "normal": 2
   },
   "layer_norm_eps": 1e-12,
   "model_type": "vit",
@@ -30,5 +30,5 @@
   "problem_type": "single_label_classification",
   "qkv_bias": true,
   "torch_dtype": "float32",
-  "transformers_version": "4.41.2"
+  "transformers_version": "4.44.2"
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7455148989b872a396003cf8cdd5907a5e9473e1b83d3be62f50cccceb5c0ff3
+oid sha256:290b15fe457b05b51b2aead184578ab5a7b5968e0c316c5ca3e47cdb48f8eaad
 size 343227052

preprocessor_config.json

@@ -1,18 +1,4 @@
 {
-  "_valid_processor_keys": [
-    "images",
-    "do_resize",
-    "size",
-    "resample",
-    "do_rescale",
-    "rescale_factor",
-    "do_normalize",
-    "image_mean",
-    "image_std",
-    "return_tensors",
-    "data_format",
-    "input_data_format"
-  ],
   "do_normalize": true,
   "do_rescale": true,
   "do_resize": true,
@@ -21,7 +7,7 @@
     0.5,
     0.5
   ],
-  "image_processor_type": "ViTFeatureExtractor",
+  "image_processor_type": "ViTImageProcessor",
   "image_std": [
     0.5,
     0.5,

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0a0785acff040118a0b3b1d19a214ad4d1bacf02743803535ee3ae239642b7da
+size 5176