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raffel-22
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emotion_classification_2_continue

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
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emotion_classification_2_continue / README.md
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metadata
license: apache-2.0
base_model: raffel-22/emotion_classification_2
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: emotion_classification_2_continue
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.725

emotion_classification_2_continue

This model is a fine-tuned version of raffel-22/emotion_classification_2 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8978
  • Accuracy: 0.725

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: 4e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 20 0.9714 0.7063
No log 2.0 40 0.9432 0.7188
No log 3.0 60 0.9633 0.7
No log 4.0 80 0.9322 0.7375
No log 5.0 100 0.8530 0.7063
No log 6.0 120 0.9063 0.7063
No log 7.0 140 0.8451 0.7125
No log 8.0 160 0.9672 0.6375
No log 9.0 180 0.9036 0.6937
No log 10.0 200 0.9261 0.6562
No log 11.0 220 0.8963 0.6937
No log 12.0 240 0.8852 0.7188
No log 13.0 260 0.8728 0.7063
No log 14.0 280 0.9559 0.6875
No log 15.0 300 0.9352 0.65
No log 16.0 320 0.8638 0.7
No log 17.0 340 0.9156 0.7
No log 18.0 360 1.0299 0.6687
No log 19.0 380 0.8983 0.675
No log 20.0 400 0.8858 0.7063
No log 21.0 420 0.9699 0.6937
No log 22.0 440 1.0603 0.625
No log 23.0 460 1.0404 0.6312
No log 24.0 480 0.8838 0.6937
0.4269 25.0 500 0.9280 0.6937
0.4269 26.0 520 0.9456 0.6937
0.4269 27.0 540 0.9640 0.6937
0.4269 28.0 560 0.9865 0.6937
0.4269 29.0 580 0.8900 0.7188
0.4269 30.0 600 0.9408 0.7063

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3