|
|
--- |
|
|
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 |
|
|
|
