End of training

README.md

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+---
+library_name: transformers
+base_model: nateraw/vit-age-classifier
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: results
+  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: 0.55
+---
+
+<!-- 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. -->
+
+# results
+
+This model is a fine-tuned version of [nateraw/vit-age-classifier](https://huggingface.co/nateraw/vit-age-classifier) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Accuracy: 0.55
+- Loss: 1.6263
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- 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
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Accuracy | Validation Loss |
+|:-------------:|:-----:|:----:|:--------:|:---------------:|
+| 2.1123        | 1.0   | 50   | 0.2412   | 2.0343          |
+| 1.8449        | 2.0   | 100  | 0.4113   | 1.7485          |
+| 1.7374        | 3.0   | 150  | 0.55     | 1.6263          |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

config.json

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+{
+  "_name_or_path": "nateraw/vit-age-classifier",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "0-2",
+    "1": "3-9",
+    "2": "10-19",
+    "3": "20-29",
+    "4": "30-39",
+    "5": "40-49",
+    "6": "50-59",
+    "7": "60-69",
+    "8": "more than 70"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0-2": 0,
+    "10-19": 2,
+    "20-29": 3,
+    "3-9": 1,
+    "30-39": 4,
+    "40-49": 5,
+    "50-59": 6,
+    "60-69": 7,
+    "more than 70": 8
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.2"
+}

model.safetensors

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+size 343245508

training_args.bin

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