End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vehicle_classification
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8466780238500852
+---
+
+<!-- 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. -->
+
+# vehicle_classification
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5738
+- Accuracy: 0.8467
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 147  | 1.4917          | 0.7785   |
+| No log        | 2.0   | 294  | 1.0285          | 0.8160   |
+| No log        | 3.0   | 441  | 0.8369          | 0.8177   |
+| 1.294         | 4.0   | 588  | 0.7112          | 0.8399   |
+| 1.294         | 5.0   | 735  | 0.6621          | 0.8313   |
+| 1.294         | 6.0   | 882  | 0.5977          | 0.8450   |
+| 0.4624        | 7.0   | 1029 | 0.5856          | 0.8518   |
+| 0.4624        | 8.0   | 1176 | 0.6511          | 0.8160   |
+| 0.4624        | 9.0   | 1323 | 0.6450          | 0.8365   |
+| 0.4624        | 10.0  | 1470 | 0.6241          | 0.8296   |
+| 0.2619        | 11.0  | 1617 | 0.6217          | 0.8382   |
+| 0.2619        | 12.0  | 1764 | 0.6504          | 0.8177   |
+| 0.2619        | 13.0  | 1911 | 0.5994          | 0.8433   |
+| 0.1776        | 14.0  | 2058 | 0.5969          | 0.8433   |
+| 0.1776        | 15.0  | 2205 | 0.5693          | 0.8569   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

runs/Feb25_16-29-51_dc813153be67/events.out.tfevents.1708880929.dc813153be67.391.1

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