Model save

README.md

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+---
+license: apache-2.0
+base_model: NekoFi/content-manage-exp2
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: portrait_cosu_exp3
+  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: 0.9148936170212766
+    - name: Precision
+      type: precision
+      value: 0.9189941972920695
+    - name: Recall
+      type: recall
+      value: 0.9148936170212766
+    - name: F1
+      type: f1
+      value: 0.9152832982620216
+---
+
+<!-- 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. -->
+
+# portrait_cosu_exp3
+
+This model is a fine-tuned version of [NekoFi/content-manage-exp2](https://huggingface.co/NekoFi/content-manage-exp2) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2524
+- Accuracy: 0.9149
+- Precision: 0.9190
+- Recall: 0.9149
+- F1: 0.9153
+- Confusion Matrix: [[19, 1], [3, 24]]
+
+## 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: 4
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Confusion Matrix   |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------------------:|
+| No log        | 0.9231 | 6    | 0.2921          | 0.8511   | 0.8527    | 0.8511 | 0.8515 | [[17, 3], [4, 23]] |
+| 0.5415        | 2.0    | 13   | 0.2564          | 0.9362   | 0.9426    | 0.9362 | 0.9353 | [[17, 3], [0, 27]] |
+| 0.5415        | 2.9231 | 19   | 0.3605          | 0.8723   | 0.8864    | 0.8723 | 0.8730 | [[19, 1], [5, 22]] |
+| 0.378         | 3.6923 | 24   | 0.2524          | 0.9149   | 0.9190    | 0.9149 | 0.9153 | [[19, 1], [3, 24]] |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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