File size: 2,423 Bytes
a983fe2 24a52ca a983fe2 24a52ca a983fe2 71e1f17 a983fe2 71e1f17 a983fe2 71e1f17 a983fe2 71e1f17 a983fe2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification
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: 0.3924731182795699
---
<!-- 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. -->
# swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co./microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0567
- Accuracy: 0.3925
## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log | 0.8889 | 6 | 2.8975 | 0.1398 |
| 2.9658 | 1.9259 | 13 | 2.6866 | 0.2204 |
| 2.6529 | 2.9630 | 20 | 2.4370 | 0.3011 |
| 2.6529 | 4.0 | 27 | 2.2516 | 0.3495 |
| 2.3311 | 4.8889 | 33 | 2.1685 | 0.3710 |
| 2.1441 | 5.9259 | 40 | 2.0987 | 0.3656 |
| 2.1441 | 6.9630 | 47 | 2.0567 | 0.3925 |
| 2.0507 | 8.0 | 54 | 2.0416 | 0.3871 |
| 1.988 | 8.8889 | 60 | 2.0368 | 0.3763 |
### Framework versions
- Transformers 4.41.2
- Pytorch 1.13.1+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
|