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resnet-50-finetuned-FER2013-0.003

This model is a fine-tuned version of microsoft/resnet-50 on the image_folder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9036
  • Accuracy: 0.6971

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: 0.003
  • 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: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.4393 1.0 224 1.2746 0.5173
1.2564 2.0 448 1.1456 0.5542
1.218 3.0 672 1.1102 0.5816
1.1919 4.0 896 1.0255 0.6151
1.1222 5.0 1120 1.0257 0.6167
1.0925 6.0 1344 0.9676 0.6317
1.0241 7.0 1568 0.9406 0.6510
1.0015 8.0 1792 0.9465 0.6532
0.987 9.0 2016 0.9002 0.6748
0.9768 10.0 2240 0.9086 0.6737
0.9408 11.0 2464 0.8975 0.6793
0.8907 12.0 2688 0.8966 0.6769
0.8051 13.0 2912 0.9142 0.6826
0.8169 14.0 3136 0.9082 0.6870
0.7729 15.0 3360 0.9036 0.6971

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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Evaluation results