End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: microsoft/resnet-50
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: resnet_aug
+  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. -->
+
+# resnet_aug
+
+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: 1.2587
+- Accuracy: 0.4686
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.6578        | 1.0   | 240  | 1.6593          | 0.2533   |
+| 1.5544        | 2.0   | 480  | 1.5545          | 0.2803   |
+| 1.4653        | 3.0   | 720  | 1.4689          | 0.3404   |
+| 1.3595        | 4.0   | 960  | 1.3931          | 0.3914   |
+| 1.2991        | 5.0   | 1200 | 1.3410          | 0.4208   |
+| 1.2512        | 6.0   | 1440 | 1.3049          | 0.4421   |
+| 1.1948        | 7.0   | 1680 | 1.2843          | 0.4552   |
+| 1.1679        | 8.0   | 1920 | 1.2667          | 0.4613   |
+| 1.1842        | 9.0   | 2160 | 1.2635          | 0.4668   |
+| 1.1268        | 10.0  | 2400 | 1.2587          | 0.4686   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Tokenizers 0.19.1

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": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5"
+  },
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5
+  },
+  "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": "4.44.2"
+}

model.safetensors

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runs/Oct19_06-57-32_60cb25ba0220/events.out.tfevents.1729321058.60cb25ba0220.5022.0

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training_args.bin

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