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aoi_clip_high_resolution_concate_fusin_crop_each_text_256

This model is a fine-tuned version of OFA-Sys/chinese-clip-vit-base-patch16 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.5401
  • Accuracy: 0.0635

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: 1e-05
  • train_batch_size: 20
  • eval_batch_size: 20
  • seed: 42
  • gradient_accumulation_steps: 10
  • total_train_batch_size: 200
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 60.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.7271 5.9821 1602 3.0070 0.0789
1.6271 11.9642 3204 3.1514 0.0732
1.552 17.9462 4806 3.1511 0.0705
1.5094 23.9283 6408 3.3706 0.0684
1.484 29.9104 8010 3.4197 0.0672
1.4683 35.8925 9612 3.5270 0.0666
1.4567 41.8745 11214 3.4933 0.0658
1.4541 47.8566 12816 3.4874 0.0653
1.4539 53.8387 14418 3.5305 0.0646
1.452 59.8208 16020 3.5401 0.0640

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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