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# 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

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