End of training

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swinv2-base-patch4-window8-256
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swinv2-base-patch4-window8-256-Kaggle_test_20231120
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.936830835117773
+---
+
+<!-- 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. -->
+
+# swinv2-base-patch4-window8-256-Kaggle_test_20231120
+
+This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1843
+- Accuracy: 0.9368
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2115        | 0.99  | 44   | 0.1843          | 0.9368   |
+| 0.1445        | 1.99  | 88   | 0.1849          | 0.9368   |
+| 0.109         | 2.98  | 132  | 0.1720          | 0.9368   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

all_results.json

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+{
+    "epoch": 2.98,
+    "eval_accuracy": 0.936830835117773,
+    "eval_loss": 0.18430249392986298,
+    "eval_runtime": 26.2491,
+    "eval_samples_per_second": 35.582,
+    "eval_steps_per_second": 2.248
+}

eval_results.json

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+{
+    "epoch": 2.98,
+    "eval_accuracy": 0.936830835117773,
+    "eval_loss": 0.18430249392986298,
+    "eval_runtime": 26.2491,
+    "eval_samples_per_second": 35.582,
+    "eval_steps_per_second": 2.248
+}

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runs/Nov20_09-41-11_2c0579f8ed20/events.out.tfevents.1700473281.2c0579f8ed20.1161.12

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