Training in progress, step 15

.gitattributes

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README.md

@@ -1,7 +1,40 @@
 ---
-library_name: keras
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: attraction-classifier
+  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: 0.7955974842767296
 ---
 
+<!-- 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. -->
+
+# attraction-classifier
+
+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: 0.4691
+- Accuracy: 0.7956
+
 ## Model description
 
 More information needed
@@ -19,23 +52,53 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 69
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.15
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6703        | 0.34  | 15   | 0.6354          | 0.7327   |
+| 0.5449        | 0.67  | 30   | 0.5836          | 0.7421   |
+| 0.5407        | 1.01  | 45   | 0.5594          | 0.7421   |
+| 0.5255        | 1.34  | 60   | 0.5294          | 0.7547   |
+| 0.5586        | 1.68  | 75   | 0.5171          | 0.7642   |
+| 0.5438        | 2.01  | 90   | 0.5212          | 0.7704   |
+| 0.4807        | 2.35  | 105  | 0.5181          | 0.7390   |
+| 0.6202        | 2.68  | 120  | 0.4972          | 0.7704   |
+| 0.5021        | 3.02  | 135  | 0.4566          | 0.7987   |
+| 0.4313        | 3.35  | 150  | 0.4852          | 0.7925   |
+| 0.3532        | 3.69  | 165  | 0.4378          | 0.8113   |
+| 0.3577        | 4.02  | 180  | 0.4515          | 0.8019   |
+| 0.4736        | 4.36  | 195  | 0.4498          | 0.7893   |
+| 0.3516        | 4.69  | 210  | 0.4408          | 0.8239   |
+| 0.4437        | 5.03  | 225  | 0.4611          | 0.7799   |
+| 0.3543        | 5.36  | 240  | 0.4294          | 0.8208   |
+| 0.4029        | 5.7   | 255  | 0.4155          | 0.8428   |
+| 0.3808        | 6.03  | 270  | 0.4116          | 0.8302   |
+| 0.3211        | 6.37  | 285  | 0.4009          | 0.8302   |
+| 0.2949        | 6.7   | 300  | 0.4321          | 0.8176   |
+| 0.2663        | 7.04  | 315  | 0.4229          | 0.8396   |
+| 0.3049        | 7.37  | 330  | 0.4110          | 0.8365   |
+| 0.1303        | 7.71  | 345  | 0.4288          | 0.8333   |
+| 0.2079        | 8.04  | 360  | 0.4218          | 0.8208   |
+| 0.208         | 8.38  | 375  | 0.3908          | 0.8365   |
+| 0.2067        | 8.72  | 390  | 0.5191          | 0.7862   |
+| 0.1635        | 9.05  | 405  | 0.4691          | 0.7956   |
+
 
-| Hyperparameters | Value |
-| :-- | :-- |
-| name | Adam |
-| weight_decay | None |
-| clipnorm | None |
-| global_clipnorm | None |
-| clipvalue | None |
-| use_ema | False |
-| ema_momentum | 0.99 |
-| ema_overwrite_frequency | None |
-| jit_compile | True |
-| is_legacy_optimizer | False |
-| learning_rate | 0.0010000000474974513 |
-| beta_1 | 0.9 |
-| beta_2 | 0.999 |
-| epsilon | 1e-07 |
-| amsgrad | False |
-| training_precision | float32 |
+### Framework versions
 
+- Transformers 4.35.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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pytorch_model.bin

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