git-base-pokemon

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: 0.0350
  • Wer Score: 2.2148

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
7.3616 4.17 50 4.5895 21.4258
2.4353 8.33 100 0.4961 9.9322
0.1527 12.5 150 0.0303 1.3197
0.0192 16.67 200 0.0260 1.3299
0.007 20.83 250 0.0297 2.2059
0.0027 25.0 300 0.0321 2.4795
0.0017 29.17 350 0.0334 2.4488
0.0014 33.33 400 0.0340 2.1355
0.0013 37.5 450 0.0345 2.3619
0.0012 41.67 500 0.0349 2.2084
0.0011 45.83 550 0.0350 2.1803
0.0011 50.0 600 0.0350 2.2148

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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