---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-in21k-finetuned-biopsy
  results: []
---

<!-- 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-base-patch16-224-in21k-finetuned-biopsy

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:
- Loss: 0.1224
- Accuracy: 0.9665

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1332        | 1.0   | 42   | 1.0712          | 0.5494   |
| 0.6556        | 2.0   | 84   | 0.5742          | 0.8492   |
| 0.3987        | 3.0   | 126  | 0.3950          | 0.8894   |
| 0.2825        | 4.0   | 168  | 0.3924          | 0.8777   |
| 0.3662        | 5.0   | 210  | 0.3622          | 0.8861   |
| 0.2218        | 6.0   | 252  | 0.2706          | 0.9246   |
| 0.2236        | 7.0   | 294  | 0.2283          | 0.9347   |
| 0.2224        | 8.0   | 336  | 0.2367          | 0.9313   |
| 0.1754        | 9.0   | 378  | 0.2139          | 0.9296   |
| 0.1707        | 10.0  | 420  | 0.1829          | 0.9497   |
| 0.1619        | 11.0  | 462  | 0.2172          | 0.9464   |
| 0.1547        | 12.0  | 504  | 0.1960          | 0.9380   |
| 0.1213        | 13.0  | 546  | 0.1484          | 0.9581   |
| 0.1388        | 14.0  | 588  | 0.1689          | 0.9581   |
| 0.1009        | 15.0  | 630  | 0.1494          | 0.9581   |
| 0.124         | 16.0  | 672  | 0.1564          | 0.9581   |
| 0.1078        | 17.0  | 714  | 0.1728          | 0.9514   |
| 0.102         | 18.0  | 756  | 0.1669          | 0.9447   |
| 0.1006        | 19.0  | 798  | 0.1405          | 0.9581   |
| 0.0791        | 20.0  | 840  | 0.1179          | 0.9665   |
| 0.0694        | 21.0  | 882  | 0.1424          | 0.9631   |
| 0.0627        | 22.0  | 924  | 0.1224          | 0.9665   |
| 0.0883        | 23.0  | 966  | 0.1602          | 0.9447   |
| 0.074         | 24.0  | 1008 | 0.1315          | 0.9615   |
| 0.0708        | 25.0  | 1050 | 0.1331          | 0.9631   |
| 0.06          | 26.0  | 1092 | 0.1191          | 0.9665   |
| 0.083         | 27.0  | 1134 | 0.1583          | 0.9531   |
| 0.0584        | 28.0  | 1176 | 0.1348          | 0.9564   |
| 0.0627        | 29.0  | 1218 | 0.1270          | 0.9564   |
| 0.0627        | 30.0  | 1260 | 0.1411          | 0.9564   |
| 0.038         | 31.0  | 1302 | 0.1208          | 0.9665   |
| 0.0569        | 32.0  | 1344 | 0.1587          | 0.9514   |
| 0.0502        | 33.0  | 1386 | 0.1501          | 0.9497   |
| 0.0464        | 34.0  | 1428 | 0.1508          | 0.9615   |
| 0.0317        | 35.0  | 1470 | 0.1309          | 0.9631   |
| 0.0552        | 36.0  | 1512 | 0.1372          | 0.9598   |
| 0.031         | 37.0  | 1554 | 0.1258          | 0.9598   |
| 0.0383        | 38.0  | 1596 | 0.1249          | 0.9682   |
| 0.036         | 39.0  | 1638 | 0.1312          | 0.9665   |
| 0.0405        | 40.0  | 1680 | 0.1207          | 0.9665   |
| 0.0343        | 41.0  | 1722 | 0.1233          | 0.9648   |
| 0.0325        | 42.0  | 1764 | 0.1286          | 0.9631   |
| 0.0293        | 43.0  | 1806 | 0.1135          | 0.9682   |
| 0.0306        | 44.0  | 1848 | 0.1258          | 0.9615   |
| 0.0267        | 45.0  | 1890 | 0.1261          | 0.9648   |
| 0.0338        | 46.0  | 1932 | 0.1209          | 0.9665   |
| 0.0213        | 47.0  | 1974 | 0.1157          | 0.9665   |
| 0.0285        | 48.0  | 2016 | 0.1203          | 0.9631   |
| 0.0287        | 49.0  | 2058 | 0.1240          | 0.9648   |
| 0.0183        | 50.0  | 2100 | 0.1224          | 0.9665   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1