msi-resnet-50

This model is a fine-tuned version of 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