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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-LongSleeveCleanedData
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9787709497206704
---
<!-- 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. -->
# resnet-50-LongSleeveCleanedData
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0889
- Accuracy: 0.9788
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9906 | 0.99 | 143 | 1.0394 | 0.6134 |
| 0.7315 | 2.0 | 287 | 0.6790 | 0.7631 |
| 0.559 | 3.0 | 431 | 0.4735 | 0.8547 |
| 0.4905 | 4.0 | 575 | 0.3148 | 0.8983 |
| 0.3465 | 5.0 | 719 | 0.2225 | 0.9363 |
| 0.3372 | 6.0 | 863 | 0.1839 | 0.9486 |
| 0.3349 | 7.0 | 1007 | 0.1617 | 0.9587 |
| 0.3159 | 7.99 | 1150 | 0.1323 | 0.9620 |
| 0.2805 | 9.0 | 1294 | 0.1660 | 0.9587 |
| 0.2657 | 10.0 | 1438 | 0.1456 | 0.9531 |
| 0.2929 | 11.0 | 1582 | 0.1086 | 0.9698 |
| 0.2763 | 12.0 | 1726 | 0.0886 | 0.9765 |
| 0.2475 | 13.0 | 1870 | 0.1041 | 0.9732 |
| 0.2148 | 14.0 | 2014 | 0.0955 | 0.9777 |
| 0.209 | 14.99 | 2157 | 0.1061 | 0.9709 |
| 0.2408 | 16.0 | 2301 | 0.0784 | 0.9743 |
| 0.222 | 17.0 | 2445 | 0.0839 | 0.9698 |
| 0.208 | 18.0 | 2589 | 0.0873 | 0.9732 |
| 0.2214 | 19.0 | 2733 | 0.0889 | 0.9788 |
| 0.2375 | 19.88 | 2860 | 0.0864 | 0.9743 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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