Model save

README.md

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+---
+library_name: transformers
+license: other
+base_model: apple/mobilevit-x-small
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: mobilevit-x-small
+  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: 0.995850622406639
+---
+
+<!-- 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. -->
+
+# mobilevit-x-small
+
+This model is a fine-tuned version of [apple/mobilevit-x-small](https://huggingface.co/apple/mobilevit-x-small) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0196
+- Accuracy: 0.9959
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6911        | 1.0   | 34   | 0.6932          | 0.5083   |
+| 0.6584        | 2.0   | 68   | 0.6287          | 0.7510   |
+| 0.5388        | 3.0   | 102  | 0.4852          | 0.8734   |
+| 0.3891        | 4.0   | 136  | 0.3065          | 0.9357   |
+| 0.2915        | 5.0   | 170  | 0.2005          | 0.9647   |
+| 0.2319        | 6.0   | 204  | 0.1498          | 0.9689   |
+| 0.2038        | 7.0   | 238  | 0.1228          | 0.9710   |
+| 0.1641        | 8.0   | 272  | 0.0892          | 0.9855   |
+| 0.1525        | 9.0   | 306  | 0.0778          | 0.9834   |
+| 0.1584        | 10.0  | 340  | 0.0565          | 0.9896   |
+| 0.1194        | 11.0  | 374  | 0.0491          | 0.9917   |
+| 0.1222        | 12.0  | 408  | 0.0436          | 0.9896   |
+| 0.1229        | 13.0  | 442  | 0.0360          | 0.9979   |
+| 0.1334        | 14.0  | 476  | 0.0326          | 0.9959   |
+| 0.122         | 15.0  | 510  | 0.0425          | 0.9896   |
+| 0.096         | 16.0  | 544  | 0.0315          | 0.9959   |
+| 0.0989        | 17.0  | 578  | 0.0303          | 0.9938   |
+| 0.1085        | 18.0  | 612  | 0.0262          | 0.9959   |
+| 0.0957        | 19.0  | 646  | 0.0232          | 0.9959   |
+| 0.1129        | 20.0  | 680  | 0.0266          | 0.9959   |
+| 0.0843        | 21.0  | 714  | 0.0234          | 0.9959   |
+| 0.0868        | 22.0  | 748  | 0.0217          | 0.9959   |
+| 0.0867        | 23.0  | 782  | 0.0233          | 0.9959   |
+| 0.0947        | 24.0  | 816  | 0.0204          | 0.9959   |
+| 0.0786        | 25.0  | 850  | 0.0199          | 0.9959   |
+| 0.1009        | 26.0  | 884  | 0.0212          | 0.9959   |
+| 0.0785        | 27.0  | 918  | 0.0204          | 0.9959   |
+| 0.0811        | 28.0  | 952  | 0.0180          | 0.9959   |
+| 0.0883        | 29.0  | 986  | 0.0193          | 0.9959   |
+| 0.0988        | 30.0  | 1020 | 0.0196          | 0.9959   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.19.1

model.safetensors

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