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image_caption_git-base_pokemon-blip-captions_finetune

This model is a fine-tuned version of microsoft/git-base on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0382
  • Wer Score: 2.2973

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Score
7.1973 4.17 50 4.4470 21.4968
2.3075 8.33 100 0.4412 10.5882
0.1359 12.5 150 0.0328 1.5792
0.0188 16.67 200 0.0293 1.1776
0.0068 20.83 250 0.0329 2.0798
0.0023 25.0 300 0.0354 2.6898
0.0014 29.17 350 0.0365 2.5650
0.0012 33.33 400 0.0374 2.4118
0.0011 37.5 450 0.0377 2.4080
0.001 41.67 500 0.0381 2.3745
0.0009 45.83 550 0.0382 2.2857
0.0009 50.0 600 0.0382 2.2973

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.0+cu117
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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