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README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-34
+tags:
+- image-classification
+- vision
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: '42'
+  results: []
+---
+
+<!-- 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. -->
+
+# 42
+
+This model is a fine-tuned version of [microsoft/resnet-34](https://huggingface.co/microsoft/resnet-34) on the cifar10 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.6750
+- Accuracy: 0.7248
+- Dt Accuracy: 0.7248
+- Df Accuracy: 0.734
+- Unlearn Overall Accuracy: 0
+- Unlearn Time: None
+
+## 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: 0.0001
+- train_batch_size: 128
+- eval_batch_size: 256
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:|
+| No log        | 1.0   | 32   | 1.9091          | 0.828    | 0.4119           | 0.4119                   | None |
+| No log        | 2.0   | 64   | 2.9815          | 0.7885   | 0.4501           | 0.4501                   | None |
+| No log        | 3.0   | 96   | 3.7770          | 0.7515   | 0                | 0                        | None |
+| No log        | 4.0   | 128  | 3.7162          | 0.754    | 0                | 0                        | None |
+| No log        | 5.0   | 160  | 4.3877          | 0.7395   | 0                | 0                        | None |
+| No log        | 6.0   | 192  | 4.8596          | 0.738    | 0                | 0                        | None |
+| No log        | 7.0   | 224  | 4.0900          | 0.727    | 0                | 0                        | None |
+| No log        | 8.0   | 256  | 4.9009          | 0.729    | 0                | 0                        | None |
+| No log        | 9.0   | 288  | 4.8932          | 0.724    | 0                | 0                        | None |
+| No log        | 10.0  | 320  | 4.6750          | 0.734    | 0                | 0                        | None |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.0
+- Tokenizers 0.15.2

all_results.json

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+{
+    "df_accuracy": 0.7885,
+    "df_loss": 2.64186692237854,
+    "dr_accuracy": 0.7927291666666667,
+    "dr_loss": 2.6324644088745117,
+    "dt_accuracy": 0.7784,
+    "epoch": 10.0,
+    "eval_unlearn_overall_accuracy": 0,
+    "knowledge_gap": 0.5018615,
+    "test_accuracy": 0.7784,
+    "test_loss": 2.9815359115600586,
+    "train_loss": 0.0,
+    "train_runtime": 130.4411,
+    "train_samples_per_second": 306.652,
+    "train_steps_per_second": 2.453,
+    "unlearn_overall_accuracy": 0.4500832219549139,
+    "unlearn_time": 130.65374088287354,
+    "zrf": 0.4906218692344466
+}

config.json

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+{
+  "_name_or_path": "../../checkpoint/cifar10/resnet-34",
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "embedding_size": 64,
+  "finetuning_task": "image-classification",
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    64,
+    128,
+    256,
+    512
+  ],
+  "id2label": {
+    "0": "airplane",
+    "1": "automobile",
+    "2": "bird",
+    "3": "cat",
+    "4": "deer",
+    "5": "dog",
+    "6": "frog",
+    "7": "horse",
+    "8": "ship",
+    "9": "truck"
+  },
+  "label2id": {
+    "airplane": "0",
+    "automobile": "1",
+    "bird": "2",
+    "cat": "3",
+    "deer": "4",
+    "dog": "5",
+    "frog": "6",
+    "horse": "7",
+    "ship": "8",
+    "truck": "9"
+  },
+  "layer_type": "basic",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "problem_type": "single_label_classification",
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2"
+}

df_results.json

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+{
+    "df_accuracy": 0.7885,
+    "df_loss": 2.64186692237854
+}

dr_results.json

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+{
+    "dr_accuracy": 0.7927291666666667,
+    "dr_loss": 2.6324644088745117
+}

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preprocessor_config.json

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+{
+  "_valid_processor_keys": [
+    "images",
+    "do_resize",
+    "size",
+    "crop_pct",
+    "resample",
+    "do_rescale",
+    "rescale_factor",
+    "do_normalize",
+    "image_mean",
+    "image_std",
+    "return_tensors",
+    "data_format",
+    "input_data_format"
+  ],
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
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+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
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+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

test_results.json

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+{
+    "test_accuracy": 0.7784,
+    "test_loss": 2.9815359115600586
+}

train_results.json

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+    "train_loss": 0.0,
+    "train_runtime": 130.4411,
+    "train_samples_per_second": 306.652,
+    "train_steps_per_second": 2.453
+}

trainer_state.json

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+  "global_step": 320,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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unlearn_final_results.json

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