File size: 2,499 Bytes
5bfdda2 1d7cc26 5bfdda2 1d7cc26 5bfdda2 1d7cc26 5bfdda2 1d7cc26 5bfdda2 1d7cc26 5bfdda2 |
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 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 |
---
library_name: transformers
license: apache-2.0
base_model: google/vit-large-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-large-patch16-224-dungeon-geo-morphs-0-4-30Nov24-008
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: dungeon-geo-morphs
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9732142857142857
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-large-patch16-224-dungeon-geo-morphs-0-4-30Nov24-008
This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the dungeon-geo-morphs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1019
- Accuracy: 0.9732
## 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:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.538 | 3.9091 | 10 | 1.2297 | 0.5982 |
| 0.7675 | 7.9091 | 20 | 0.5668 | 0.9321 |
| 0.2383 | 11.9091 | 30 | 0.2734 | 0.95 |
| 0.0619 | 15.9091 | 40 | 0.1570 | 0.9643 |
| 0.0172 | 19.9091 | 50 | 0.1019 | 0.9732 |
| 0.0058 | 23.9091 | 60 | 0.0944 | 0.9696 |
| 0.0031 | 27.9091 | 70 | 0.0848 | 0.9714 |
| 0.0024 | 31.9091 | 80 | 0.0830 | 0.9714 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|