Add model

.gitignore

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+checkpoint-*/

README.md

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+---
+tags:
+- image-classification
+- timm
+- generated_from_trainer
+datasets:
+- beans
+model-index:
+- name: model
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: beans
+      type: beans
+      args: default
+library_tag: timm
+---
+
+<!-- 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. -->
+
+# model
+
+This model is a fine-tuned version of [resnet18](https://huggingface.co/resnet18) on the beans dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0219
+- Acc1: 56.3910
+- Acc5: 100.0
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 20
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.10.2
+- Pytorch 1.7.1
+- Datasets 1.12.1
+- Tokenizers 0.10.3

all_results.json

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+{
+    "epoch": 0.15,
+    "eval_acc1": 56.39097595214844,
+    "eval_acc5": 100.0,
+    "eval_loss": 1.0218992233276367,
+    "eval_runtime": 1.7151,
+    "eval_samples_per_second": 77.547,
+    "eval_steps_per_second": 9.912,
+    "train_loss": 1.065065288543701,
+    "train_runtime": 13.903,
+    "train_samples_per_second": 11.508,
+    "train_steps_per_second": 1.439
+}

config.json

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+{
+  "url": "https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnet50_ram-a26f946b.pth",
+  "num_classes": 3,
+  "input_size": [
+    3,
+    224,
+    224
+  ],
+  "pool_size": [
+    7,
+    7
+  ],
+  "crop_pct": 0.875,
+  "interpolation": "bicubic",
+  "mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "first_conv": "conv1",
+  "classifier": "fc",
+  "architecture": "resnet50",
+  "num_features": 2048,
+  "labels": [
+    "angular_leaf_spot",
+    "bean_rust",
+    "healthy"
+  ]
+}

eval_results.json

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+{
+    "epoch": 0.15,
+    "eval_acc1": 56.39097595214844,
+    "eval_acc5": 100.0,
+    "eval_loss": 1.0218992233276367,
+    "eval_runtime": 1.7151,
+    "eval_samples_per_second": 77.547,
+    "eval_steps_per_second": 9.912
+}

pytorch_model.bin

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train_results.json

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+{
+    "epoch": 0.15,
+    "train_loss": 1.065065288543701,
+    "train_runtime": 13.903,
+    "train_samples_per_second": 11.508,
+    "train_steps_per_second": 1.439
+}

trainer_state.json

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+  "epoch": 0.15384615384615385,
+  "global_step": 20,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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+      "train_runtime": 13.903,
+      "train_samples_per_second": 11.508,
+      "train_steps_per_second": 1.439
+    }
+  ],
+  "max_steps": 20,
+  "num_train_epochs": 1,
+  "total_flos": 0.0,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

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