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GIT-naruto

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metadata
license: mit
base_model: microsoft/git-base
tags:
  - generated_from_trainer
model-index:
  - name: GIT-naruto
    results: []

GIT-naruto

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

  • Loss: 0.0774
  • Wer Score: 16.0923

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: 1
  • eval_batch_size: 1
  • seed: 42
  • 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
7.4722 0.93 50 4.5072 21.6154
2.1729 1.85 100 0.3006 0.5077
0.0896 2.78 150 0.0626 0.6154
0.0296 3.7 200 0.0647 21.7538
0.0228 4.63 250 0.0599 21.7077
0.0169 5.56 300 0.0627 3.5846
0.0162 6.48 350 0.0611 17.0769
0.0147 7.41 400 0.0649 21.6769
0.0131 8.33 450 0.0631 15.0154
0.0119 9.26 500 0.0668 19.3231
0.0117 10.19 550 0.0645 20.3231
0.0106 11.11 600 0.0631 21.6308
0.0099 12.04 650 0.0655 17.6923
0.0098 12.96 700 0.0662 18.0615
0.0092 13.89 750 0.0656 18.1385
0.0089 14.81 800 0.0658 21.6615
0.0086 15.74 850 0.0677 20.4
0.0079 16.67 900 0.0684 21.6462
0.0085 17.59 950 0.0701 21.6615
0.0089 18.52 1000 0.0716 16.8923
0.0083 19.44 1050 0.0685 21.6769
0.0079 20.37 1100 0.0665 21.7077
0.0075 21.3 1150 0.0685 19.5231
0.0078 22.22 1200 0.0669 20.7385
0.0078 23.15 1250 0.0677 18.6923
0.007 24.07 1300 0.0698 19.7231
0.008 25.0 1350 0.0682 20.4769
0.0073 25.93 1400 0.0705 19.3231
0.008 26.85 1450 0.0738 21.6615
0.0071 27.78 1500 0.0722 19.9231
0.0064 28.7 1550 0.0731 21.6923
0.0063 29.63 1600 0.0741 20.5385
0.0069 30.56 1650 0.0780 19.8462
0.0063 31.48 1700 0.0763 16.9538
0.0061 32.41 1750 0.0775 19.7846
0.0062 33.33 1800 0.0772 19.1077
0.0065 34.26 1850 0.0737 17.7231
0.0062 35.19 1900 0.0752 19.5385
0.0058 36.11 1950 0.0748 19.4
0.006 37.04 2000 0.0752 18.4154
0.0053 37.96 2050 0.0746 17.1385
0.0053 38.89 2100 0.0766 15.8154
0.0052 39.81 2150 0.0770 17.2
0.0049 40.74 2200 0.0763 19.3538
0.0051 41.67 2250 0.0766 19.9692
0.0046 42.59 2300 0.0768 19.9846
0.0045 43.52 2350 0.0773 16.3692
0.0044 44.44 2400 0.0771 16.7846
0.0041 45.37 2450 0.0773 17.6308
0.0042 46.3 2500 0.0774 16.0615
0.0041 47.22 2550 0.0767 16.3231
0.004 48.15 2600 0.0771 16.1846
0.0037 49.07 2650 0.0772 16.0462
0.0035 50.0 2700 0.0774 16.0923

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.16.1
  • Tokenizers 0.15.1