|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: resnet-18-finetuned-eurosat |
|
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. --> |
|
|
|
# resnet-18-finetuned-eurosat |
|
|
|
This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5506 |
|
- Accuracy: 0.8364 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.3846 | 0.99 | 20 | 0.6352 | 0.7576 | |
|
| 0.5009 | 1.98 | 40 | 0.6439 | 0.7485 | |
|
| 0.5625 | 2.96 | 60 | 0.5722 | 0.7909 | |
|
| 0.4928 | 4.0 | 81 | 0.5514 | 0.7970 | |
|
| 0.4621 | 4.99 | 101 | 0.6104 | 0.7697 | |
|
| 0.4367 | 5.98 | 121 | 0.5734 | 0.7939 | |
|
| 0.4238 | 6.96 | 141 | 0.5558 | 0.8 | |
|
| 0.4011 | 8.0 | 162 | 0.5549 | 0.8030 | |
|
| 0.4129 | 8.99 | 182 | 0.5554 | 0.8061 | |
|
| 0.384 | 9.98 | 202 | 0.5551 | 0.8152 | |
|
| 0.3839 | 10.96 | 222 | 0.5742 | 0.8091 | |
|
| 0.3496 | 12.0 | 243 | 0.5518 | 0.8303 | |
|
| 0.3482 | 12.99 | 263 | 0.5390 | 0.8303 | |
|
| 0.357 | 13.98 | 283 | 0.5544 | 0.8182 | |
|
| 0.3341 | 14.96 | 303 | 0.5506 | 0.8364 | |
|
| 0.3605 | 16.0 | 324 | 0.5546 | 0.8212 | |
|
| 0.3041 | 16.99 | 344 | 0.5597 | 0.8212 | |
|
| 0.3364 | 17.98 | 364 | 0.5730 | 0.8091 | |
|
| 0.2976 | 18.96 | 384 | 0.5742 | 0.8091 | |
|
| 0.3229 | 19.75 | 400 | 0.5653 | 0.8121 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.1 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
