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nymiz-model-nuextract-pjcr-es-api

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

  • Loss: 0.6077

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: 0.0002
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 3407
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 5
  • num_epochs: 6

Training results

Training Loss Epoch Step Validation Loss
0.6028 0.9905 26 0.6623
0.2973 1.9810 52 0.6077
0.2814 2.9714 78 0.6485
0.168 4.0 105 0.6724
0.0565 4.9905 131 0.7278
0.0445 5.9429 156 0.7434

Framework versions

  • PEFT 0.11.1
  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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