xtremedistil-l6-h256-uncased: OCR-quality-classification

This model is a fine-tuned version of microsoft/xtremedistil-l6-h256-uncased on pszemraj/OCR-quality-classification

It achieves the following results on the evaluation set:

  • Loss: 0.0316
  • Accuracy: 0.994
  • Num Input Tokens Seen: 57341952

Intended uses & limitations

predict whether a document is clean or noisy

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 3e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 2.0

Training results

Training Loss Epoch Step Validation Loss Accuracy Input Tokens Seen
0.0812 0.2660 250 0.0860 0.986 8192000
0.0637 0.5321 500 0.0532 0.988 16384000
0.031 0.7981 750 0.0463 0.99 24576000
0.0315 1.0641 1000 0.0343 0.992 32765952
0.0223 1.3301 1250 0.0337 0.994 40957952
0.0137 1.5962 1500 0.0423 0.99 49149952
0.0186 1.8622 1750 0.0316 0.994 57341952

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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