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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Entrnal_5class_agumm_last_newV6_model |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# Entrnal_5class_agumm_last_newV6_model |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0410 |
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- Train Accuracy: 0.9612 |
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- Train Top-3-accuracy: 0.9962 |
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- Validation Loss: 0.3703 |
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- Validation Accuracy: 0.9623 |
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- Validation Top-3-accuracy: 0.9963 |
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- Epoch: 12 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 1209, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch | |
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|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:| |
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| 1.0109 | 0.5898 | 0.8913 | 0.5771 | 0.7468 | 0.9576 | 0 | |
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| 0.4103 | 0.7997 | 0.9708 | 0.4029 | 0.8329 | 0.9786 | 1 | |
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| 0.2249 | 0.8581 | 0.9827 | 0.3677 | 0.8769 | 0.9857 | 2 | |
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| 0.1584 | 0.8905 | 0.9877 | 0.3730 | 0.9010 | 0.9893 | 3 | |
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| 0.1164 | 0.9097 | 0.9904 | 0.3957 | 0.9169 | 0.9913 | 4 | |
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| 0.0841 | 0.9231 | 0.9920 | 0.3896 | 0.9285 | 0.9927 | 5 | |
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| 0.0676 | 0.9331 | 0.9932 | 0.3718 | 0.9373 | 0.9937 | 6 | |
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| 0.0561 | 0.9408 | 0.9941 | 0.3701 | 0.9440 | 0.9944 | 7 | |
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| 0.0500 | 0.9468 | 0.9947 | 0.3691 | 0.9493 | 0.9949 | 8 | |
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| 0.0461 | 0.9516 | 0.9952 | 0.3698 | 0.9535 | 0.9954 | 9 | |
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| 0.0435 | 0.9554 | 0.9956 | 0.3694 | 0.9570 | 0.9958 | 10 | |
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| 0.0418 | 0.9585 | 0.9959 | 0.3705 | 0.9598 | 0.9961 | 11 | |
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| 0.0410 | 0.9612 | 0.9962 | 0.3703 | 0.9623 | 0.9963 | 12 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- TensorFlow 2.15.1 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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