Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: google-vit-base-patch16-224-Waste-O-I-classification
+  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: 0.956
+---
+
+<!-- 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. -->
+
+# google-vit-base-patch16-224-Waste-O-I-classification
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Accuracy: 0.956
+- Loss: 0.3036
+
+## 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: 0.0002
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Accuracy | Validation Loss |
+|:-------------:|:------:|:-----:|:--------:|:---------------:|
+| 0.2168        | 0.1580 | 1000  | 0.9525   | 0.1303          |
+| 0.196         | 0.3159 | 2000  | 0.941    | 0.1638          |
+| 0.1993        | 0.4739 | 3000  | 0.9285   | 0.2206          |
+| 0.1849        | 0.6318 | 4000  | 0.9225   | 0.2288          |
+| 0.199         | 0.7898 | 5000  | 0.9105   | 0.3331          |
+| 0.2171        | 0.9477 | 6000  | 0.944    | 0.1582          |
+| 0.1209        | 1.1057 | 7000  | 0.9495   | 0.1887          |
+| 0.114         | 1.2636 | 8000  | 0.932    | 0.1950          |
+| 0.1268        | 1.4216 | 9000  | 0.9335   | 0.1965          |
+| 0.1272        | 1.5795 | 10000 | 0.9165   | 0.3112          |
+| 0.1003        | 1.7375 | 11000 | 0.9575   | 0.1353          |
+| 0.0844        | 1.8954 | 12000 | 0.9345   | 0.2635          |
+| 0.0757        | 2.0534 | 13000 | 0.952    | 0.1434          |
+| 0.053         | 2.2113 | 14000 | 0.933    | 0.3203          |
+| 0.0994        | 2.3693 | 15000 | 0.9405   | 0.2165          |
+| 0.0248        | 2.5272 | 16000 | 0.951    | 0.2400          |
+| 0.0842        | 2.6852 | 17000 | 0.906    | 0.4092          |
+| 0.0733        | 2.8432 | 18000 | 0.9515   | 0.1937          |
+| 0.0542        | 3.0011 | 19000 | 0.938    | 0.2911          |
+| 0.0202        | 3.1591 | 20000 | 0.936    | 0.3648          |
+| 0.0237        | 3.3170 | 21000 | 0.9355   | 0.3618          |
+| 0.0294        | 3.4750 | 22000 | 0.9255   | 0.4209          |
+| 0.0375        | 3.6329 | 23000 | 0.943    | 0.2840          |
+| 0.0176        | 3.7909 | 24000 | 0.9525   | 0.2604          |
+| 0.0252        | 3.9488 | 25000 | 0.9515   | 0.2500          |
+| 0.0024        | 4.1068 | 26000 | 0.9545   | 0.2892          |
+| 0.0119        | 4.2647 | 27000 | 0.956    | 0.3036          |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0+cpu
+- Datasets 2.20.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 5.0,
+    "eval_accuracy": 0.941,
+    "eval_loss": 0.3915315866470337,
+    "eval_model_preparation_time": 0.006,
+    "eval_runtime": 1091.8268,
+    "eval_samples_per_second": 1.832,
+    "eval_steps_per_second": 0.229,
+    "total_flos": 1.962407144999928e+19,
+    "train_loss": 0.005569123022438927,
+    "train_runtime": 203795.3117,
+    "train_samples_per_second": 1.243,
+    "train_steps_per_second": 0.155
+}

eval_results.json

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+{
+    "epoch": 5.0,
+    "eval_accuracy": 0.941,
+    "eval_loss": 0.3915315866470337,
+    "eval_runtime": 1091.8268,
+    "eval_samples_per_second": 1.832,
+    "eval_steps_per_second": 0.229
+}

train_results.json

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+{
+    "epoch": 5.0,
+    "total_flos": 1.962407144999928e+19,
+    "train_loss": 0.005569123022438927,
+    "train_runtime": 203795.3117,
+    "train_samples_per_second": 1.243,
+    "train_steps_per_second": 0.155
+}