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NPL-experiment-agl

This model is a fine-tuned version of distilroberta-base on the datasetX dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5756
  • Accuracy: 0.8211
  • F1: 0.8726

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.5059 1.09 500 0.5756 0.8211 0.8726
0.3299 2.18 1000 0.7190 0.8309 0.8761

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.13.3
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Dataset used to train Alejandro-sin/NPL-experiment-agl

Evaluation results