End of training

README.md

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+---
+base_model: swin-tiny-patch4-window7-224
+tags:
+- image-classification
+- timm
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swin-tiny-patch4-window7-224_ft_mango_leaf_disease
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: mango_leaf_disease
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9916666666666667
+---
+
+<!-- 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. -->
+
+# swin-tiny-patch4-window7-224_ft_mango_leaf_disease
+
+This model is a fine-tuned version of [swin-tiny-patch4-window7-224](https://huggingface.co/swin-tiny-patch4-window7-224) on the mango_leaf_disease dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1712
+- Accuracy: 0.9917
+
+## 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: 1e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 143
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.93  | 10   | 0.6785          | 0.9306   |
+| No log        | 1.95  | 21   | 0.3613          | 0.9736   |
+| No log        | 2.98  | 32   | 0.2289          | 0.9847   |
+| No log        | 4.0   | 43   | 0.1783          | 0.9917   |
+| No log        | 4.65  | 50   | 0.1712          | 0.9917   |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

all_results.json

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+{
+    "epoch": 4.65,
+    "test_accuracy": 1.0,
+    "test_loss": 0.16256704926490784,
+    "test_runtime": 19.1855,
+    "test_samples_per_second": 9.382,
+    "test_steps_per_second": 0.156,
+    "total_flos": 3.1303908690827674e+17,
+    "train_loss": 0.40170501708984374,
+    "train_runtime": 365.1652,
+    "train_samples_per_second": 36.97,
+    "train_steps_per_second": 0.137
+}

config.json

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+{
+  "_name_or_path": "/content/swin-tiny-patch4-window7-224-mango_leaf_disease-2023-10-01",
+  "architectures": [
+    "SwinForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "depths": [
+    2,
+    2,
+    6,
+    2
+  ],
+  "drop_path_rate": 0.1,
+  "embed_dim": 96,
+  "encoder_stride": 32,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Anthracnose",
+    "1": "Bacterial Canker",
+    "2": "Cutting Weevil",
+    "3": "Die Back",
+    "4": "Gall Midge",
+    "5": "Healthy",
+    "6": "Powdery Mildew",
+    "7": "Sooty Mould"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "Anthracnose": "0",
+    "Bacterial Canker": "1",
+    "Cutting Weevil": "2",
+    "Die Back": "3",
+    "Gall Midge": "4",
+    "Healthy": "5",
+    "Powdery Mildew": "6",
+    "Sooty Mould": "7"
+  },
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 4.0,
+  "model_type": "swin",
+  "num_channels": 3,
+  "num_heads": [
+    3,
+    6,
+    12,
+    24
+  ],
+  "num_layers": 4,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "patch_size": 4,
+  "path_norm": true,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.3",
+  "use_absolute_embeddings": false,
+  "window_size": 7
+}

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

pytorch_model.bin

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test_results.json

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+{
+    "epoch": 4.65,
+    "test_accuracy": 1.0,
+    "test_loss": 0.16256704926490784,
+    "test_runtime": 19.1855,
+    "test_samples_per_second": 9.382,
+    "test_steps_per_second": 0.156
+}

train_results.json

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+{
+    "epoch": 4.65,
+    "total_flos": 3.1303908690827674e+17,
+    "train_loss": 0.40170501708984374,
+    "train_runtime": 365.1652,
+    "train_samples_per_second": 36.97,
+    "train_steps_per_second": 0.137
+}

trainer_state.json

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+{
+  "best_metric": 0.9916666666666667,
+  "best_model_checkpoint": "swin-tiny-patch4-window7-224-mango_leaf_disease-2023-10-01/checkpoint-43",
+  "epoch": 4.651162790697675,
+  "eval_steps": 500,
+  "global_step": 50,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.93,
+      "eval_accuracy": 0.9305555555555556,
+      "eval_loss": 0.6785286664962769,
+      "eval_runtime": 74.8256,
+      "eval_samples_per_second": 9.622,
+      "eval_steps_per_second": 0.16,
+      "step": 10
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+    {
+      "epoch": 1.95,
+      "eval_accuracy": 0.9736111111111111,
+      "eval_loss": 0.3613281548023224,
+      "eval_runtime": 1.8755,
+      "eval_samples_per_second": 383.906,
+      "eval_steps_per_second": 6.398,
+      "step": 21
+    },
+    {
+      "epoch": 2.98,
+      "eval_accuracy": 0.9847222222222223,
+      "eval_loss": 0.22890280187129974,
+      "eval_runtime": 1.8891,
+      "eval_samples_per_second": 381.125,
+      "eval_steps_per_second": 6.352,
+      "step": 32
+    },
+    {
+      "epoch": 4.0,
+      "eval_accuracy": 0.9916666666666667,
+      "eval_loss": 0.17830978333950043,
+      "eval_runtime": 1.8501,
+      "eval_samples_per_second": 389.168,
+      "eval_steps_per_second": 6.486,
+      "step": 43
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+    {
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+      "eval_accuracy": 0.9916666666666667,
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+      "eval_runtime": 1.8622,
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+      "eval_steps_per_second": 6.444,
+      "step": 50
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+    {
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+      "total_flos": 3.1303908690827674e+17,
+      "train_loss": 0.40170501708984374,
+      "train_runtime": 365.1652,
+      "train_samples_per_second": 36.97,
+      "train_steps_per_second": 0.137
+    }
+  ],
+  "logging_steps": 500,
+  "max_steps": 50,
+  "num_train_epochs": 5,
+  "save_steps": 500,
+  "total_flos": 3.1303908690827674e+17,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

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