|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: resnet-50-finetuned-nct-crc-he-45k |
|
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: 0.9788888888888889 |
|
--- |
|
|
|
<!-- 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-50-finetuned-nct-crc-he-45k |
|
|
|
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0704 |
|
- Accuracy: 0.9789 |
|
|
|
## 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: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.6319 | 1.0 | 246 | 1.5910 | 0.8181 | |
|
| 0.335 | 2.0 | 492 | 0.2492 | 0.9397 | |
|
| 0.2563 | 3.0 | 738 | 0.1462 | 0.9613 | |
|
| 0.2055 | 4.0 | 985 | 0.1201 | 0.9679 | |
|
| 0.1713 | 5.0 | 1231 | 0.1003 | 0.9719 | |
|
| 0.1575 | 6.0 | 1477 | 0.1020 | 0.9722 | |
|
| 0.1293 | 7.0 | 1723 | 0.0817 | 0.9747 | |
|
| 0.1104 | 8.0 | 1970 | 0.0798 | 0.9779 | |
|
| 0.1552 | 9.0 | 2216 | 0.0851 | 0.9763 | |
|
| 0.1267 | 9.99 | 2460 | 0.0704 | 0.9789 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.1 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.10.0 |
|
- Tokenizers 0.13.2 |
|
|
