git-base-ww

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: 0.5035
  • Wer Score: 6.7310

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Score
3.6106 3.128 50 4.5591 9.3966
1.2545 6.256 100 0.8047 3.2328
0.2342 9.384 150 0.4631 0.9336
0.1497 12.512 200 0.4565 1.2560
0.106 15.64 250 0.4637 2.1828
0.0813 18.768 300 0.4687 2.2207
0.0612 21.896 350 0.4750 6.5422
0.0536 25.0 400 0.4805 6.7198
0.0426 28.128 450 0.4867 2.6293
0.0361 31.256 500 0.4890 7.3362
0.031 34.384 550 0.4939 7.0353
0.0267 37.512 600 0.5003 2.7284
0.0241 40.64 650 0.5009 6.9310
0.0227 43.768 700 0.5015 6.9078
0.021 46.896 750 0.5036 6.7776
0.0203 50.0 800 0.5035 6.7310

Framework versions

  • Transformers 4.52.4
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.2
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