Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-50
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: resnet-50-finetuned-cifar10
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.5022
+---
+
+<!-- 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. -->
+
+# resnet-50-finetuned-cifar10
+
+This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9064
+- Accuracy: 0.5022
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.3058        | 0.03  | 10   | 2.3106          | 0.0794   |
+| 2.3033        | 0.06  | 20   | 2.3026          | 0.0892   |
+| 2.3012        | 0.09  | 30   | 2.2971          | 0.1042   |
+| 2.2914        | 0.11  | 40   | 2.2890          | 0.1254   |
+| 2.2869        | 0.14  | 50   | 2.2816          | 0.16     |
+| 2.2785        | 0.17  | 60   | 2.2700          | 0.1902   |
+| 2.2712        | 0.2   | 70   | 2.2602          | 0.2354   |
+| 2.2619        | 0.23  | 80   | 2.2501          | 0.2688   |
+| 2.2509        | 0.26  | 90   | 2.2383          | 0.3022   |
+| 2.2382        | 0.28  | 100  | 2.2229          | 0.3268   |
+| 2.2255        | 0.31  | 110  | 2.2084          | 0.353    |
+| 2.2164        | 0.34  | 120  | 2.1939          | 0.3608   |
+| 2.2028        | 0.37  | 130  | 2.1829          | 0.3668   |
+| 2.1977        | 0.4   | 140  | 2.1646          | 0.401    |
+| 2.1844        | 0.43  | 150  | 2.1441          | 0.4244   |
+| 2.1689        | 0.45  | 160  | 2.1323          | 0.437    |
+| 2.1555        | 0.48  | 170  | 2.1159          | 0.4462   |
+| 2.1448        | 0.51  | 180  | 2.0992          | 0.45     |
+| 2.1313        | 0.54  | 190  | 2.0810          | 0.4642   |
+| 2.1189        | 0.57  | 200  | 2.0589          | 0.4708   |
+| 2.1111        | 0.6   | 210  | 2.0430          | 0.4828   |
+| 2.0905        | 0.63  | 220  | 2.0288          | 0.4938   |
+| 2.082         | 0.65  | 230  | 2.0089          | 0.4938   |
+| 2.0646        | 0.68  | 240  | 1.9970          | 0.5014   |
+| 2.0636        | 0.71  | 250  | 1.9778          | 0.4946   |
+| 2.0579        | 0.74  | 260  | 1.9609          | 0.49     |
+| 2.028         | 0.77  | 270  | 1.9602          | 0.4862   |
+| 2.0447        | 0.8   | 280  | 1.9460          | 0.4934   |
+| 2.0168        | 0.82  | 290  | 1.9369          | 0.505    |
+| 2.0126        | 0.85  | 300  | 1.9317          | 0.4926   |
+| 2.0099        | 0.88  | 310  | 1.9235          | 0.4952   |
+| 1.9978        | 0.91  | 320  | 1.9174          | 0.4972   |
+| 1.9951        | 0.94  | 330  | 1.9119          | 0.507    |
+| 1.9823        | 0.97  | 340  | 1.9120          | 0.4992   |
+| 1.985         | 1.0   | 350  | 1.9064          | 0.5022   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.1
+- Datasets 2.14.6
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "microsoft/resnet-50",
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "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": "bottleneck",
+  "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": "4.35.0"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9d68b1283c09e88286fb9621b92e917ceef1e2f9354101412f90e8b66ef796a0
+size 94368544

preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

training_args.bin

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+size 4600