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# msi-resnet-50

This model is a fine-tuned version of [Nubletz/msi-resnet-pretrain](https://huggingface.co/Nubletz/msi-resnet-pretrain) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 29628148372356011655168.0000
- eval_accuracy: 0.5662
- eval_runtime: 362.9719
- eval_samples_per_second: 78.838
- eval_steps_per_second: 4.929
- epoch: 5.0
- step: 10078

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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

### Framework versions

- Transformers 4.36.1
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

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