---
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