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rendchevi/mental-longformer-base-4096-pr

sourceHugging Facecc-by-nc-4.0updated 10mo agoView on Hugging Face
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mental-longformer-base-4096-pr

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

  • —Loss: 0.9954
  • —F1 Macro: 0.6043
  • —Precision: 0.6255
  • —Recall: 0.6059
  • —Accuracy: 0.7596

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 log1.02401.97920.38990.42160.42640.6217
No log2.04800.86160.57350.59060.60190.7399
1.88623.07200.87250.58530.59950.61550.7320
1.88624.09600.81290.61370.60300.63260.7534
0.86335.012000.88690.60560.62060.61810.7622
0.86336.014400.99540.60430.62550.60590.7596

Framework versions

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