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---
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: '2024_08_13'
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: 0.75
---
<!-- 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. -->
# 2024_08_13
This model was trained from scratch on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6787
- Accuracy: 0.75
## 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: 1e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.7191 | 0.992 | 31 | 0.7459 | 0.25 |
| 0.6894 | 1.984 | 62 | 0.6787 | 0.75 |
| 0.5993 | 2.976 | 93 | 0.6090 | 0.75 |
| 0.5858 | 4.0 | 125 | 0.5702 | 0.75 |
| 0.5407 | 4.992 | 156 | 0.5572 | 0.75 |
| 0.6552 | 5.984 | 187 | 0.5553 | 0.75 |
| 0.5562 | 6.976 | 218 | 0.5529 | 0.75 |
| 0.6054 | 8.0 | 250 | 0.5519 | 0.75 |
| 0.7563 | 8.992 | 281 | 0.5518 | 0.75 |
| 0.5174 | 9.984 | 312 | 0.5523 | 0.75 |
| 0.3765 | 10.9760 | 343 | 0.5514 | 0.75 |
| 0.5727 | 12.0 | 375 | 0.5507 | 0.75 |
| 0.5613 | 12.992 | 406 | 0.5510 | 0.75 |
| 0.568 | 13.984 | 437 | 0.5510 | 0.75 |
| 0.6655 | 14.9760 | 468 | 0.5514 | 0.75 |
| 0.4883 | 16.0 | 500 | 0.5522 | 0.75 |
| 0.5317 | 16.992 | 531 | 0.5518 | 0.75 |
| 0.4501 | 17.984 | 562 | 0.5520 | 0.75 |
| 0.4616 | 18.976 | 593 | 0.5519 | 0.75 |
| 0.4522 | 20.0 | 625 | 0.5510 | 0.75 |
| 0.6326 | 20.992 | 656 | 0.5507 | 0.75 |
| 0.3828 | 21.984 | 687 | 0.5508 | 0.75 |
| 0.4283 | 22.976 | 718 | 0.5509 | 0.75 |
| 0.6701 | 24.0 | 750 | 0.5506 | 0.75 |
| 0.6157 | 24.992 | 781 | 0.5503 | 0.75 |
| 0.5657 | 25.984 | 812 | 0.5503 | 0.75 |
| 0.5127 | 26.976 | 843 | 0.5503 | 0.75 |
| 0.6178 | 28.0 | 875 | 0.5503 | 0.75 |
| 0.5679 | 28.992 | 906 | 0.5502 | 0.75 |
| 0.6102 | 29.76 | 930 | 0.5502 | 0.75 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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