End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: jaffe_V2_50
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8
+---
+
+<!-- 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. -->
+
+# jaffe_V2_50
+
+This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7217
+- Accuracy: 0.8
+
+## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 1    | 1.9638          | 0.2333   |
+| No log        | 2.0   | 2    | 1.7893          | 0.3333   |
+| No log        | 3.0   | 3    | 1.8759          | 0.1667   |
+| No log        | 4.0   | 4    | 1.6759          | 0.3667   |
+| No log        | 5.0   | 5    | 1.5139          | 0.5      |
+| No log        | 6.0   | 6    | 1.4280          | 0.5667   |
+| No log        | 7.0   | 7    | 1.3688          | 0.5667   |
+| No log        | 8.0   | 8    | 1.2819          | 0.6      |
+| No log        | 9.0   | 9    | 1.1884          | 0.6      |
+| 1.5329        | 10.0  | 10   | 1.1448          | 0.6      |
+| 1.5329        | 11.0  | 11   | 1.0732          | 0.7      |
+| 1.5329        | 12.0  | 12   | 0.9793          | 0.7333   |
+| 1.5329        | 13.0  | 13   | 0.8830          | 0.7333   |
+| 1.5329        | 14.0  | 14   | 0.8366          | 0.7667   |
+| 1.5329        | 15.0  | 15   | 0.8027          | 0.7333   |
+| 1.5329        | 16.0  | 16   | 0.7952          | 0.7333   |
+| 1.5329        | 17.0  | 17   | 0.7746          | 0.7333   |
+| 1.5329        | 18.0  | 18   | 0.7571          | 0.7667   |
+| 1.5329        | 19.0  | 19   | 0.7256          | 0.7667   |
+| 0.5232        | 20.0  | 20   | 0.7217          | 0.8      |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.3.1
+- Tokenizers 0.21.0

runs/Mar09_18-45-26_5e64d5cc0472/events.out.tfevents.1741545927.5e64d5cc0472.31.0

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