End of training

README.md

@@ -1,15 +1,66 @@
 ---
-license: mit
-datasets:
-- Sisigoks/Food_Database_MK1
-language:
-- en
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
 metrics:
 - accuracy
-base_model:
-- google/vit-base-patch16-224
-- google/vit-base-patch16-224-in21k
-pipeline_tag: image-classification
-tags:
-- food
----
+model-index:
+- name: Food_Classifer_NoviceMK-I
+  results: []
+---
+
+<!-- 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. -->
+
+# Food_Classifer_NoviceMK-I
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 5.9452
+- Accuracy: 0.2332
+
+## 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
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 6.1717        | 1.0   | 138  | 6.1566          | 0.0915   |
+| 5.972         | 2.0   | 276  | 5.9996          | 0.2065   |
+| 5.8591        | 3.0   | 414  | 5.9452          | 0.2332   |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0