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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- f1
model-index:
- name: 6-classifier-finetuned-padchest
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: F1
type: f1
value: 0.7990439256526214
---
<!-- 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. -->
# 6-classifier-finetuned-padchest
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6407
- F1: 0.7990
## 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 | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.0829 | 1.0 | 18 | 2.0240 | 0.1072 |
| 1.9599 | 2.0 | 36 | 1.8375 | 0.3757 |
| 1.725 | 3.0 | 54 | 1.5851 | 0.4462 |
| 1.5014 | 4.0 | 72 | 1.3785 | 0.4928 |
| 1.3135 | 5.0 | 90 | 1.2678 | 0.5368 |
| 1.2446 | 6.0 | 108 | 1.1646 | 0.6053 |
| 1.1576 | 7.0 | 126 | 1.1553 | 0.5554 |
| 1.0868 | 8.0 | 144 | 1.0353 | 0.6231 |
| 1.0121 | 9.0 | 162 | 1.0081 | 0.6435 |
| 0.988 | 10.0 | 180 | 0.9306 | 0.6951 |
| 0.9663 | 11.0 | 198 | 0.9062 | 0.7062 |
| 0.8709 | 12.0 | 216 | 0.8939 | 0.6950 |
| 0.8891 | 13.0 | 234 | 0.8283 | 0.7371 |
| 0.843 | 14.0 | 252 | 0.7945 | 0.7482 |
| 0.8339 | 15.0 | 270 | 0.8384 | 0.7236 |
| 0.8029 | 16.0 | 288 | 0.8167 | 0.7426 |
| 0.777 | 17.0 | 306 | 0.7842 | 0.7659 |
| 0.7592 | 18.0 | 324 | 0.8064 | 0.7427 |
| 0.7052 | 19.0 | 342 | 0.7804 | 0.7553 |
| 0.7556 | 20.0 | 360 | 0.7332 | 0.7851 |
| 0.688 | 21.0 | 378 | 0.7643 | 0.7676 |
| 0.7216 | 22.0 | 396 | 0.7391 | 0.7623 |
| 0.6434 | 23.0 | 414 | 0.6996 | 0.7869 |
| 0.6673 | 24.0 | 432 | 0.7297 | 0.7775 |
| 0.6474 | 25.0 | 450 | 0.7006 | 0.7807 |
| 0.6352 | 26.0 | 468 | 0.7134 | 0.7778 |
| 0.6068 | 27.0 | 486 | 0.7377 | 0.7776 |
| 0.5942 | 28.0 | 504 | 0.6723 | 0.8089 |
| 0.5945 | 29.0 | 522 | 0.6686 | 0.7941 |
| 0.603 | 30.0 | 540 | 0.6667 | 0.7809 |
| 0.5974 | 31.0 | 558 | 0.6698 | 0.7946 |
| 0.5743 | 32.0 | 576 | 0.6531 | 0.8090 |
| 0.5663 | 33.0 | 594 | 0.6756 | 0.8013 |
| 0.5583 | 34.0 | 612 | 0.6535 | 0.8025 |
| 0.5199 | 35.0 | 630 | 0.6542 | 0.7936 |
| 0.5851 | 36.0 | 648 | 0.6595 | 0.7956 |
| 0.5105 | 37.0 | 666 | 0.6784 | 0.7886 |
| 0.4947 | 38.0 | 684 | 0.6625 | 0.8002 |
| 0.5197 | 39.0 | 702 | 0.6637 | 0.7975 |
| 0.514 | 40.0 | 720 | 0.6527 | 0.7925 |
| 0.4949 | 41.0 | 738 | 0.6482 | 0.7992 |
| 0.5047 | 42.0 | 756 | 0.6427 | 0.8036 |
| 0.5058 | 43.0 | 774 | 0.6437 | 0.8052 |
| 0.4645 | 44.0 | 792 | 0.6324 | 0.8062 |
| 0.4411 | 45.0 | 810 | 0.6481 | 0.8052 |
| 0.4602 | 46.0 | 828 | 0.6460 | 0.8037 |
| 0.4265 | 47.0 | 846 | 0.6505 | 0.8036 |
| 0.4945 | 48.0 | 864 | 0.6467 | 0.7991 |
| 0.4794 | 49.0 | 882 | 0.6388 | 0.8084 |
| 0.442 | 50.0 | 900 | 0.6407 | 0.7990 |
### Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.13.3
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