Training in progress, step 500

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-50
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: freeway_resnet50_Model
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/zbrisuho)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/zbrisuho)
+# freeway_resnet50_Model
+
+This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0047
+- Accuracy: 1.0
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 0.3403        | 0.4808  | 100  | 0.3006          | 0.9454   |
+| 0.3093        | 0.9615  | 200  | 0.2498          | 0.9540   |
+| 0.2743        | 1.4423  | 300  | 0.2004          | 0.9666   |
+| 0.2375        | 1.9231  | 400  | 0.1552          | 0.9798   |
+| 0.2118        | 2.4038  | 500  | 0.1143          | 0.9852   |
+| 0.1953        | 2.8846  | 600  | 0.1095          | 0.9844   |
+| 0.1807        | 3.3654  | 700  | 0.0893          | 0.9895   |
+| 0.1623        | 3.8462  | 800  | 0.0682          | 0.9914   |
+| 0.1414        | 4.3269  | 900  | 0.0560          | 0.9941   |
+| 0.1296        | 4.8077  | 1000 | 0.0511          | 0.9933   |
+| 0.1195        | 5.2885  | 1100 | 0.0344          | 0.9957   |
+| 0.1114        | 5.7692  | 1200 | 0.0303          | 0.9984   |
+| 0.1034        | 6.25    | 1300 | 0.0298          | 0.9965   |
+| 0.0994        | 6.7308  | 1400 | 0.0257          | 0.9987   |
+| 0.0907        | 7.2115  | 1500 | 0.0225          | 0.9992   |
+| 0.0881        | 7.6923  | 1600 | 0.0201          | 0.9987   |
+| 0.0801        | 8.1731  | 1700 | 0.0157          | 1.0      |
+| 0.0764        | 8.6538  | 1800 | 0.0141          | 0.9995   |
+| 0.0746        | 9.1346  | 1900 | 0.0142          | 0.9995   |
+| 0.0715        | 9.6154  | 2000 | 0.0115          | 0.9995   |
+| 0.074         | 10.0962 | 2100 | 0.0124          | 0.9992   |
+| 0.0677        | 10.5769 | 2200 | 0.0102          | 0.9995   |
+| 0.0679        | 11.0577 | 2300 | 0.0101          | 0.9995   |
+| 0.068         | 11.5385 | 2400 | 0.0110          | 0.9992   |
+| 0.0589        | 12.0192 | 2500 | 0.0081          | 0.9997   |
+| 0.0581        | 12.5    | 2600 | 0.0090          | 0.9995   |
+| 0.058         | 12.9808 | 2700 | 0.0080          | 0.9995   |
+| 0.0559        | 13.4615 | 2800 | 0.0082          | 0.9997   |
+| 0.0547        | 13.9423 | 2900 | 0.0062          | 1.0      |
+| 0.0493        | 14.4231 | 3000 | 0.0061          | 1.0      |
+| 0.0506        | 14.9038 | 3100 | 0.0054          | 1.0      |
+| 0.0466        | 15.3846 | 3200 | 0.0068          | 0.9995   |
+| 0.0506        | 15.8654 | 3300 | 0.0055          | 1.0      |
+| 0.0481        | 16.3462 | 3400 | 0.0053          | 1.0      |
+| 0.0523        | 16.8269 | 3500 | 0.0053          | 1.0      |
+| 0.0537        | 17.3077 | 3600 | 0.0061          | 0.9995   |
+| 0.0474        | 17.7885 | 3700 | 0.0049          | 1.0      |
+| 0.0511        | 18.2692 | 3800 | 0.0054          | 1.0      |
+| 0.0474        | 18.75   | 3900 | 0.0052          | 1.0      |
+| 0.0456        | 19.2308 | 4000 | 0.0062          | 0.9997   |
+| 0.0385        | 19.7115 | 4100 | 0.0047          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.42.0.dev0
+- Pytorch 2.1.1
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "facebook/convnextv2-tiny-22k-224",
+  "architectures": [
+    "ConvNextV2ForImageClassification"
+  ],
+  "depths": [
+    3,
+    3,
+    9,
+    3
+  ],
+  "drop_path_rate": 0.0,
+  "hidden_act": "gelu",
+  "hidden_sizes": [
+    96,
+    192,
+    384,
+    768
+  ],
+  "id2label": {
+    "0": "0",
+    "1": "1"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "0": 0,
+    "1": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "convnextv2",
+  "num_channels": 3,
+  "num_stages": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "patch_size": 4,
+  "problem_type": "single_label_classification",
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.0.dev0"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a081e1fd136b852d34e866612ed0aebdc3e83c08b3400698461e5c0a28026551
+size 111495808

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": false,
+  "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 5112