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--- |
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license: apache-2.0 |
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base_model: microsoft/resnet-50 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: SaladSlayer00/twin_matcher_beta |
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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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# SaladSlayer00/twin_matcher_beta |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0286 |
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- Validation Loss: 1.1866 |
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- Validation Accuracy: 0.7159 |
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- Epoch: 34 |
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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': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, '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 | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:---------------:|:-------------------:|:-----:| |
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| 7.0814 | 4.8848 | 0.0133 | 0 | |
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| 4.6679 | 4.5568 | 0.0666 | 1 | |
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| 4.3536 | 4.1337 | 0.1221 | 2 | |
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| 3.8915 | 3.6650 | 0.2053 | 3 | |
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| 3.4256 | 3.2568 | 0.2597 | 4 | |
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| 3.0033 | 2.8885 | 0.3185 | 5 | |
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| 2.6252 | 2.5913 | 0.3973 | 6 | |
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| 2.2829 | 2.3391 | 0.4406 | 7 | |
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| 1.9821 | 2.1352 | 0.4928 | 8 | |
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| 1.7076 | 1.9428 | 0.5250 | 9 | |
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| 1.4693 | 1.8008 | 0.5627 | 10 | |
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| 1.2464 | 1.6763 | 0.5949 | 11 | |
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| 1.0552 | 1.5872 | 0.6093 | 12 | |
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| 0.9105 | 1.4840 | 0.6238 | 13 | |
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| 0.7595 | 1.4117 | 0.6426 | 14 | |
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| 0.6390 | 1.3601 | 0.6582 | 15 | |
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| 0.5328 | 1.3283 | 0.6548 | 16 | |
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| 0.4539 | 1.2958 | 0.6681 | 17 | |
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| 0.3655 | 1.2470 | 0.6715 | 18 | |
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| 0.3183 | 1.2389 | 0.6770 | 19 | |
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| 0.2597 | 1.2309 | 0.6792 | 20 | |
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| 0.2269 | 1.2193 | 0.6881 | 21 | |
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| 0.1750 | 1.2206 | 0.6781 | 22 | |
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| 0.1553 | 1.1853 | 0.6970 | 23 | |
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| 0.1313 | 1.1949 | 0.6781 | 24 | |
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| 0.1058 | 1.1935 | 0.6870 | 25 | |
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| 0.0903 | 1.2042 | 0.6859 | 26 | |
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| 0.0762 | 1.1950 | 0.6948 | 27 | |
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| 0.0654 | 1.1798 | 0.7037 | 28 | |
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| 0.0588 | 1.1955 | 0.6959 | 29 | |
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| 0.0488 | 1.1788 | 0.7048 | 30 | |
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| 0.0444 | 1.1845 | 0.7037 | 31 | |
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| 0.0374 | 1.1969 | 0.7026 | 32 | |
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| 0.0327 | 1.1907 | 0.7048 | 33 | |
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| 0.0286 | 1.1866 | 0.7159 | 34 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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