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---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_keras_callback
model-index:
- name: SaladSlayer00/twin_matcher_beta
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# SaladSlayer00/twin_matcher_beta
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0286
- Validation Loss: 1.1866
- Validation Accuracy: 0.7159
- Epoch: 34
## 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:
- 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}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:---------------:|:-------------------:|:-----:|
| 7.0814 | 4.8848 | 0.0133 | 0 |
| 4.6679 | 4.5568 | 0.0666 | 1 |
| 4.3536 | 4.1337 | 0.1221 | 2 |
| 3.8915 | 3.6650 | 0.2053 | 3 |
| 3.4256 | 3.2568 | 0.2597 | 4 |
| 3.0033 | 2.8885 | 0.3185 | 5 |
| 2.6252 | 2.5913 | 0.3973 | 6 |
| 2.2829 | 2.3391 | 0.4406 | 7 |
| 1.9821 | 2.1352 | 0.4928 | 8 |
| 1.7076 | 1.9428 | 0.5250 | 9 |
| 1.4693 | 1.8008 | 0.5627 | 10 |
| 1.2464 | 1.6763 | 0.5949 | 11 |
| 1.0552 | 1.5872 | 0.6093 | 12 |
| 0.9105 | 1.4840 | 0.6238 | 13 |
| 0.7595 | 1.4117 | 0.6426 | 14 |
| 0.6390 | 1.3601 | 0.6582 | 15 |
| 0.5328 | 1.3283 | 0.6548 | 16 |
| 0.4539 | 1.2958 | 0.6681 | 17 |
| 0.3655 | 1.2470 | 0.6715 | 18 |
| 0.3183 | 1.2389 | 0.6770 | 19 |
| 0.2597 | 1.2309 | 0.6792 | 20 |
| 0.2269 | 1.2193 | 0.6881 | 21 |
| 0.1750 | 1.2206 | 0.6781 | 22 |
| 0.1553 | 1.1853 | 0.6970 | 23 |
| 0.1313 | 1.1949 | 0.6781 | 24 |
| 0.1058 | 1.1935 | 0.6870 | 25 |
| 0.0903 | 1.2042 | 0.6859 | 26 |
| 0.0762 | 1.1950 | 0.6948 | 27 |
| 0.0654 | 1.1798 | 0.7037 | 28 |
| 0.0588 | 1.1955 | 0.6959 | 29 |
| 0.0488 | 1.1788 | 0.7048 | 30 |
| 0.0444 | 1.1845 | 0.7037 | 31 |
| 0.0374 | 1.1969 | 0.7026 | 32 |
| 0.0327 | 1.1907 | 0.7048 | 33 |
| 0.0286 | 1.1866 | 0.7159 | 34 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.0
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