|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: microsoft/swin-base-patch4-window7-224 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: swin-finetuned-class_mi_a4c |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- 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-finetuned-class_mi_a4c |
|
|
|
|
|
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 187691964027097262850048.0000 |
|
|
- Accuracy: 0.4324 |
|
|
|
|
|
## 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: 0.001 |
|
|
- train_batch_size: 8 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 4 |
|
|
- total_train_batch_size: 32 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: reduce_lr_on_plateau |
|
|
- lr_scheduler_warmup_ratio: 0.1 |
|
|
- num_epochs: 10 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|
|:-----------------------------:|:-----:|:----:|:-----------------------------:|:--------:| |
|
|
| No log | 0.84 | 4 | 187691964027097262850048.0000 | 0.4324 | |
|
|
| No log | 1.89 | 9 | 187691964027097262850048.0000 | 0.4324 | |
|
|
| 197383793291431707148288.0000 | 2.95 | 14 | 187691964027097262850048.0000 | 0.4324 | |
|
|
| 197383793291431707148288.0000 | 4.0 | 19 | 187691964027097262850048.0000 | 0.4324 | |
|
|
| 201517492465567910592512.0000 | 4.84 | 23 | 187691964027097262850048.0000 | 0.4324 | |
|
|
| 201517492465567910592512.0000 | 5.89 | 28 | 187691964027097262850048.0000 | 0.4324 | |
|
|
| 190149859368370083725312.0000 | 6.95 | 33 | 187691964027097262850048.0000 | 0.4324 | |
|
|
| 190149859368370083725312.0000 | 8.0 | 38 | 187691964027097262850048.0000 | 0.4324 | |
|
|
| 203584363669914227048448.0000 | 8.42 | 40 | 187691964027097262850048.0000 | 0.4324 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.36.2 |
|
|
- Pytorch 2.1.2+cu118 |
|
|
- Datasets 2.15.0 |
|
|
- Tokenizers 0.15.0 |
|
|
|
