File size: 2,270 Bytes
f980e41 a5e9f80 f980e41 620d16f 437116b 691adc1 96ddd24 788cf3e 9f56c08 bbbdb17 0402123 f64943c 64b3aed 0e30910 eff7ecd a5e9f80 f980e41 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
---
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: 0.9105
- Validation Loss: 1.4840
- Validation Accuracy: 0.6238
- Epoch: 13
## 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 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.0
|