resnet-50_finetuned / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: resnet-50_finetuned
    results: []

resnet-50_finetuned

This model is a fine-tuned version of microsoft/resnet-50 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7209
  • Precision: 0.3702
  • Recall: 0.5
  • F1: 0.4254
  • Accuracy: 0.7404

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 46 0.6599 0.3702 0.5 0.4254 0.7404
No log 2.0 92 0.6725 0.3702 0.5 0.4254 0.7404
No log 3.0 138 nan 0.8714 0.5062 0.4384 0.7436
No log 4.0 184 nan 0.8714 0.5062 0.4384 0.7436
No log 5.0 230 nan 0.8714 0.5062 0.4384 0.7436
No log 6.0 276 nan 0.8714 0.5062 0.4384 0.7436
No log 7.0 322 nan 0.8714 0.5062 0.4384 0.7436
No log 8.0 368 nan 0.8714 0.5062 0.4384 0.7436
No log 9.0 414 nan 0.8714 0.5062 0.4384 0.7436
No log 10.0 460 0.7209 0.3702 0.5 0.4254 0.7404

Framework versions

  • Transformers 4.22.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.5.1
  • Tokenizers 0.12.1