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-2
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: beans
+      type: beans
+      args: default
+    metric:
+      name: Accuracy
+      type: accuracy
+      value: 0.5789473684210527
+---
+
+<!-- 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-2
+
+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: 1.3225
+- Accuracy: 0.5789
+
+## 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: 0.001
+- train_batch_size: 4
+- 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
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2601        | 0.02  | 5    | 2.8349          | 0.5113   |
+| 1.8184        | 0.04  | 10   | 1.3225          | 0.5789   |
+
+
+### 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": 0.04,
+    "eval_accuracy": 0.5789473684210527,
+    "eval_loss": 1.3225154876708984,
+    "eval_runtime": 7.4355,
+    "eval_samples_per_second": 17.887,
+    "eval_steps_per_second": 2.286,
+    "train_loss": 2.0306697309017183,
+    "train_runtime": 22.46,
+    "train_samples_per_second": 1.781,
+    "train_steps_per_second": 0.445
+}

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": 0.04,
+    "eval_accuracy": 0.5789473684210527,
+    "eval_loss": 1.3225154876708984,
+    "eval_runtime": 7.4355,
+    "eval_samples_per_second": 17.887,
+    "eval_steps_per_second": 2.286
+}

pytorch_model.bin

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train_results.json

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+    "train_samples_per_second": 1.781,
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+}

trainer_state.json

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+  "best_model_checkpoint": "./timm-resnet18-beans-test-2/checkpoint-10",
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+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
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+}

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