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_g004
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train[:90]
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7777777777777778
urinary_carcinoma_classifier_g004
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: 0.5556
- Accuracy: 0.7778
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.8 | 1 | 0.6989 | 0.6111 |
| No log | 1.6 | 2 | 0.6758 | 0.6111 |
| No log | 2.4 | 3 | 0.6409 | 0.6667 |
| No log | 4.0 | 5 | 0.6102 | 0.7222 |
| No log | 4.8 | 6 | 0.6065 | 0.7778 |
| No log | 5.6 | 7 | 0.6030 | 0.7778 |
| No log | 6.4 | 8 | 0.6254 | 0.5556 |
| 0.6126 | 8.0 | 10 | 0.5948 | 0.7222 |
| 0.6126 | 8.8 | 11 | 0.5967 | 0.6667 |
| 0.6126 | 9.6 | 12 | 0.5784 | 0.7778 |
| 0.6126 | 10.4 | 13 | 0.5751 | 0.6667 |
| 0.6126 | 12.0 | 15 | 0.5556 | 0.7778 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1