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emotion-classificationV3

This model is a fine-tuned version of /content/model/emotion-classificationV3/checkpoint-60 on FastJobs/Visual_Emotional_Analysis Dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5765
  • Accuracy: 0.8438

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

FastJobs/Visual_Emotional_Analysis

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 143
  • 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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 5 0.6923 0.7937
0.5541 2.0 10 0.7871 0.8063
0.5541 3.0 15 0.7193 0.8313
0.5168 4.0 20 0.6446 0.825
0.5168 5.0 25 0.5653 0.8438
0.4627 6.0 30 0.7244 0.8063
0.4627 7.0 35 0.7213 0.7937
0.4516 8.0 40 0.6082 0.8313
0.4516 9.0 45 0.7545 0.8063
0.4339 10.0 50 0.5320 0.8562
0.4339 11.0 55 0.6222 0.8187
0.4233 12.0 60 0.6104 0.8438
0.4233 13.0 65 0.5913 0.825
0.3976 14.0 70 0.6852 0.8125
0.3976 15.0 75 0.6227 0.8125
0.3933 16.0 80 0.5550 0.825
0.3933 17.0 85 0.5438 0.8438
0.4359 18.0 90 0.5916 0.825
0.4359 19.0 95 0.6037 0.8063
0.3589 20.0 100 0.7102 0.8125

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Model size
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F32
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