add model

.gitignore

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+checkpoint-*/

README.md

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+---
+tags:
+- image-classification
+- timm
+- generated_from_trainer
+datasets:
+- beans
+metrics:
+- accuracy
+model_index:
+- name: timm-resnet18-beans-test
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: beans
+      type: beans
+      args: default
+    metric:
+      name: Accuracy
+      type: accuracy
+      value: 0.3609022556390977
+---
+
+<!-- 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. -->
+
+# timm-resnet18-beans-test
+
+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: 1.2126
+- Accuracy: 0.3609
+
+## 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: 10
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.9.1
+- Pytorch 1.9.0
+- Datasets 1.11.1.dev0
+- Tokenizers 0.10.3

all_results.json

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+{
+    "epoch": 0.08,
+    "eval_accuracy": 0.3609022556390977,
+    "eval_loss": 1.2125978469848633,
+    "eval_runtime": 7.8732,
+    "eval_samples_per_second": 16.893,
+    "eval_steps_per_second": 2.159,
+    "train_loss": 1.1646986961364747,
+    "train_runtime": 15.1084,
+    "train_samples_per_second": 5.295,
+    "train_steps_per_second": 0.662
+}

config.json

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+{"url": "https://download.pytorch.org/models/resnet18-5c106cde.pth", "num_classes": 1000, "input_size": [3, 224, 224], "pool_size": [7, 7], "crop_pct": 0.875, "interpolation": "bilinear", "mean": [0.485, 0.456, 0.406], "std": [0.229, 0.224, 0.225], "first_conv": "conv1", "classifier": "fc", "architecture": "resnet18"}

eval_results.json

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+{
+    "epoch": 0.08,
+    "eval_accuracy": 0.3609022556390977,
+    "eval_loss": 1.2125978469848633,
+    "eval_runtime": 7.8732,
+    "eval_samples_per_second": 16.893,
+    "eval_steps_per_second": 2.159
+}

pytorch_model.bin

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train_results.json

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+{
+    "epoch": 0.08,
+    "train_loss": 1.1646986961364747,
+    "train_runtime": 15.1084,
+    "train_samples_per_second": 5.295,
+    "train_steps_per_second": 0.662
+}

trainer_state.json

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+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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+  "max_steps": 10,
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+  "total_flos": 0.0,
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+  "trial_params": null
+}

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