File size: 1,790 Bytes
7e499e2 e2a0ba1 7e499e2 e2a0ba1 7e499e2 e2a0ba1 7e499e2 e2a0ba1 7e499e2 e2a0ba1 7e499e2 e2a0ba1 | 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 | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: frncscp/patacoptimus-prime
results: []
datasets:
- frncscp/patacon-730
metrics:
- accuracy
---
<!-- 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. -->
# frncscp/patacoptimus-prime
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on [frncscp/patacon-730](https://huggingface.co/datasets/frncscp/patacon-730).
It achieves the following results on the evaluation set:
- Train Loss: 0.0043
- Validation Loss: 0.0086
- Train Accuracy: 0.9977
- Epoch: 14
## Model description
One-Class Patacognition Transformer
## Intended uses & limitations
It was designed for One-Class Patacón Classification
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 34960, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.0064 | 0.0079 | 0.9977 | 0 |
| 0.0043 | 0.0086 | 0.9977 | 1 |
### Framework versions
- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3 |