File size: 2,431 Bytes
91d79b2 |
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 70 71 |
---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: VIT_fourclass_classifier
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. -->
# VIT_fourclass_classifier
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0945
- Validation Loss: 1.7241
- Train Accuracy: 0.6974
- Epoch: 14
## 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': 'SGD', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': np.float32(0.01), 'momentum': 0.0, 'nesterov': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.7946 | 1.1484 | 0.6272 | 0 |
| 0.3246 | 1.1792 | 0.6769 | 1 |
| 0.2266 | 1.2812 | 0.6842 | 2 |
| 0.1841 | 1.5085 | 0.6754 | 3 |
| 0.1589 | 1.4224 | 0.6944 | 4 |
| 0.1244 | 1.4229 | 0.6901 | 5 |
| 0.1174 | 1.4858 | 0.6784 | 6 |
| 0.1133 | 1.4221 | 0.6974 | 7 |
| 0.1026 | 1.4273 | 0.7003 | 8 |
| 0.1083 | 1.5406 | 0.7003 | 9 |
| 0.1038 | 1.6223 | 0.6974 | 10 |
| 0.0876 | 1.5613 | 0.6959 | 11 |
| 0.1018 | 1.4540 | 0.7149 | 12 |
| 0.0808 | 1.4853 | 0.7193 | 13 |
| 0.0945 | 1.7241 | 0.6974 | 14 |
### Framework versions
- Transformers 4.52.4
- TensorFlow 2.18.0
- Datasets 3.6.0
- Tokenizers 0.21.1
|