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rendchevi/longformer-base-4096-tqacd

sourceHugging Faceapache-2.0updated 10mo agoView on Hugging Face
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longformer-base-4096-tqacd

This model is a fine-tuned version of allenai/longformer-base-4096 on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 2.8100
  • —F1 Macro: 0.2577
  • —Precision: 0.2667
  • —Recall: 0.2705
  • —Accuracy: 0.3663

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: 2e-05
  • —trainbatchsize: 16
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 20
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossF1 MacroPrecisionRecallAccuracy
No log1.01142.40050.01560.00860.09090.0941
No log2.02282.32640.16110.15670.20070.3663
No log3.03422.24060.16080.17060.22380.2079
No log4.04562.23280.19050.20130.21660.3317
2.24265.05702.23080.24920.26480.29900.3069
2.24266.06842.33850.26940.30770.30010.3515
2.24267.07982.48070.27560.31710.28760.3960
2.24268.09122.55910.27120.28080.30500.3020
0.97699.010262.81000.25770.26670.27050.3663

Framework versions

  • —Transformers 4.57.1
  • —Pytorch 2.8.0+cu128
  • —Datasets 4.4.1
  • —Tokenizers 0.22.1