heado

README.md

@@ -2,8 +2,9 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
-- image-classification
 - ViT
+- HHD
+- image-classification
 - generated_from_trainer
 metrics:
 - accuracy
@@ -19,7 +20,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the beans dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0205
+- Loss: 0.0148
 - Accuracy: 1.0
 
 ## Model description
@@ -52,13 +53,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.091         | 1.5385 | 100  | 0.0747          | 0.9774   |
-| 0.036         | 3.0769 | 200  | 0.0205          | 1.0      |
+| 0.056         | 1.5385 | 100  | 0.0564          | 0.9850   |
+| 0.0375        | 3.0769 | 200  | 0.0148          | 1.0      |
 
 
 ### Framework versions
 
-- Transformers 4.41.2
-- Pytorch 2.3.0+cu121
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
 - Datasets 2.20.0
 - Tokenizers 0.19.1

config.json

@@ -30,5 +30,5 @@
   "problem_type": "single_label_classification",
   "qkv_bias": true,
   "torch_dtype": "float32",
-  "transformers_version": "4.41.2"
+  "transformers_version": "4.42.4"
 }

model.safetensors

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 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,

runs/Jul30_00-50-27_c1a0f3ceb19c/events.out.tfevents.1722301819.c1a0f3ceb19c.179.0

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training_args.bin

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