End of training

README.md

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+---
+library_name: transformers
+base_model: gerbejon/webpage_labeling_classifier
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: webpage_labeling_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: 0.9416466826538769
+---
+
+<!-- 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. -->
+
+# webpage_labeling_classifier
+
+This model is a fine-tuned version of [gerbejon/webpage_labeling_classifier](https://huggingface.co/gerbejon/webpage_labeling_classifier) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1555
+- Accuracy: 0.9416
+
+## 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: 20
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 0.2002        | 0.9968  | 78   | 0.1917          | 0.9281   |
+| 0.2191        | 1.9936  | 156  | 0.2132          | 0.9097   |
+| 0.2067        | 2.9904  | 234  | 0.2522          | 0.9065   |
+| 0.1751        | 4.0     | 313  | 0.1931          | 0.9217   |
+| 0.1346        | 4.9968  | 391  | 0.1933          | 0.9241   |
+| 0.1448        | 5.9936  | 469  | 0.1816          | 0.9313   |
+| 0.1389        | 6.9904  | 547  | 0.2027          | 0.9209   |
+| 0.1387        | 8.0     | 626  | 0.1696          | 0.9384   |
+| 0.1234        | 8.9968  | 704  | 0.1758          | 0.9345   |
+| 0.1196        | 9.9936  | 782  | 0.1848          | 0.9305   |
+| 0.1213        | 10.9904 | 860  | 0.1769          | 0.9400   |
+| 0.1287        | 12.0    | 939  | 0.1421          | 0.9488   |
+| 0.117         | 12.9968 | 1017 | 0.2046          | 0.9241   |
+| 0.1433        | 13.9936 | 1095 | 0.1769          | 0.9369   |
+| 0.0988        | 14.9904 | 1173 | 0.1494          | 0.9496   |
+| 0.1136        | 16.0    | 1252 | 0.1571          | 0.9424   |
+| 0.086         | 16.9968 | 1330 | 0.1712          | 0.9384   |
+| 0.089         | 17.9936 | 1408 | 0.1437          | 0.9440   |
+| 0.0991        | 18.9904 | 1486 | 0.1510          | 0.9448   |
+| 0.0824        | 19.9361 | 1560 | 0.1555          | 0.9416   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

model.safetensors

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