resnet-18-resnet-18

This model is a fine-tuned version of microsoft/resnet-18 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 5878685290980833992550249398272.0000
• Accuracy: 0.3542

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
No log	0.8889	6	5256596847186447919144532705280.0000	0.3542
6252348666680642391375611953152.0000	1.9259	13	5816409290772115792559022800896.0000	0.3542
5941338476045271956843984322560.0000	2.9630	20	5569209952566045840858865991680.0000	0.3542
5941338476045271956843984322560.0000	4.0	27	5764530657074993210784856670208.0000	0.3542
5978113032337293509815187800064.0000	4.8889	33	5717174614869048956753266343936.0000	0.3542
6377920275134342219963975073792.0000	5.9259	40	5885479454087068208512098107392.0000	0.3542
6377920275134342219963975073792.0000	6.9630	47	5693683372805207289944963284992.0000	0.3542
6201930657158778429750307192832.0000	8.0	54	5815479022353922335409086398464.0000	0.3542
6266525497982100125501481811968.0000	8.8889	60	5878685290980833992550249398272.0000	0.3542

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1