metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: urinary_carcinoma_classifier_g001
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train[:23]
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6
urinary_carcinoma_classifier_g001
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6827
- Accuracy: 0.6
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 1 | 0.7147 | 0.4 |
No log | 2.0 | 2 | 0.7114 | 0.4 |
No log | 3.0 | 3 | 0.6968 | 0.2 |
No log | 4.0 | 4 | 0.7055 | 0.4 |
No log | 5.0 | 5 | 0.6741 | 0.4 |
No log | 6.0 | 6 | 0.6580 | 0.6 |
No log | 7.0 | 7 | 0.6092 | 0.6 |
No log | 8.0 | 8 | 0.6200 | 0.6 |
No log | 9.0 | 9 | 0.6139 | 0.6 |
0.3094 | 10.0 | 10 | 0.5969 | 0.6 |
0.3094 | 11.0 | 11 | 0.5677 | 0.6 |
0.3094 | 12.0 | 12 | 0.6021 | 0.6 |
0.3094 | 13.0 | 13 | 0.6189 | 0.6 |
0.3094 | 14.0 | 14 | 0.6054 | 0.6 |
0.3094 | 15.0 | 15 | 0.6240 | 0.6 |
0.3094 | 16.0 | 16 | 0.5388 | 0.6 |
0.3094 | 17.0 | 17 | 0.5320 | 0.6 |
0.3094 | 18.0 | 18 | 0.5973 | 0.6 |
0.3094 | 19.0 | 19 | 0.5981 | 0.8 |
0.1723 | 20.0 | 20 | 0.6531 | 0.6 |
0.1723 | 21.0 | 21 | 0.6246 | 0.6 |
0.1723 | 22.0 | 22 | 0.6718 | 0.6 |
0.1723 | 23.0 | 23 | 0.6692 | 0.6 |
0.1723 | 24.0 | 24 | 0.6537 | 0.6 |
0.1723 | 25.0 | 25 | 0.4650 | 0.6 |
0.1723 | 26.0 | 26 | 0.6873 | 0.6 |
0.1723 | 27.0 | 27 | 0.6461 | 0.6 |
0.1723 | 28.0 | 28 | 0.5876 | 0.8 |
0.1723 | 29.0 | 29 | 0.4898 | 0.6 |
0.1049 | 30.0 | 30 | 0.6827 | 0.6 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1