File size: 2,101 Bytes
567e405 a6bc06a 567e405 590a554 567e405 86af37d a6d9cc0 b9e3e3c 77674e5 89e05ba b5e7274 68cc3c7 f2ddda0 06487ae 22e7fa7 590a554 567e405 a6bc06a 567e405 |
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 |
---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_keras_callback
model-index:
- name: SaladSlayer00/image_classification_resnet
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/image_classification_resnet
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: 1.4845
- Validation Loss: 1.7643
- Validation Accuracy: 0.5666
- Epoch: 10
## 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 |
|:----------:|:---------------:|:-------------------:|:-----:|
| 7.0750 | 4.8746 | 0.0090 | 0 |
| 4.6468 | 4.5229 | 0.0538 | 1 |
| 4.3211 | 4.1033 | 0.1209 | 2 |
| 3.8784 | 3.6736 | 0.1859 | 3 |
| 3.4274 | 3.2193 | 0.2419 | 4 |
| 3.0071 | 2.8524 | 0.3012 | 5 |
| 2.6239 | 2.5632 | 0.3651 | 6 |
| 2.2925 | 2.2959 | 0.4233 | 7 |
| 1.9792 | 2.1138 | 0.4882 | 8 |
| 1.7199 | 1.9271 | 0.5174 | 9 |
| 1.4845 | 1.7643 | 0.5666 | 10 |
### Framework versions
- Transformers 4.36.2
- TensorFlow 2.15.0
- Datasets 2.16.0
- Tokenizers 0.15.0
|