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enoriega/rule_learning_test

sourceHugging Faceapache-2.0updated 4y agoView on Hugging Face
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Model Card

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rulelearningtest

This model is a fine-tuned version of bert-base-uncased on the enoriega/odinsynth_dataset dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1255

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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 1000
  • —totaltrainbatch_size: 8000
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 3.0
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
0.17640.32200.2303
0.1450.64400.1470
0.1290.96600.1321
0.12561.29800.1265
0.13041.611000.1252
0.12351.931200.1260
0.1252.261400.1261
0.12632.581600.1262
0.12442.91800.1256

Framework versions

  • —Transformers 4.19.2
  • —Pytorch 1.11.0
  • —Datasets 2.2.1
  • —Tokenizers 0.12.1