Model save

README.md

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+---
+license: apache-2.0
+base_model: NekoFi/portrait_cosu_exp3
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: portrait_cosu_exp4
+  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: 0.9037037037037037
+    - name: Precision
+      type: precision
+      value: 0.9042846124813338
+    - name: Recall
+      type: recall
+      value: 0.9037037037037037
+    - name: F1
+      type: f1
+      value: 0.9035443167305236
+---
+
+<!-- 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_exp4
+
+This model is a fine-tuned version of [NekoFi/portrait_cosu_exp3](https://huggingface.co/NekoFi/portrait_cosu_exp3) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2432
+- Accuracy: 0.9037
+- Precision: 0.9043
+- Recall: 0.9037
+- F1: 0.9035
+- Confusion Matrix: [[66, 5], [8, 56]]
+
+## 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    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------------------:|
+| 0.3876        | 1.0   | 19   | 0.3650          | 0.8370   | 0.8555    | 0.8370 | 0.8336 | [[68, 3], [19, 45]] |
+| 0.2696        | 2.0   | 38   | 0.2479          | 0.8963   | 0.8965    | 0.8963 | 0.8962 | [[65, 6], [8, 56]]  |
+| 0.2143        | 3.0   | 57   | 0.2665          | 0.8889   | 0.8906    | 0.8889 | 0.8885 | [[66, 5], [10, 54]] |
+| 0.1629        | 4.0   | 76   | 0.2432          | 0.9037   | 0.9043    | 0.9037 | 0.9035 | [[66, 5], [8, 56]]  |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1