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chiabingxuan/v2-heladepdet-bert-finetuned-regression

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face
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v2-heladepdet-bert-finetuned-regression

This model is a fine-tuned version of google-bert/bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.2472
  • —Mse: 0.6236

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: 0.0001
  • —trainbatchsize: 32
  • —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
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossMse
2.09110.57342501.51800.7590
1.48131.14685001.45770.7289
1.39261.72027501.36900.6845
1.35872.293610001.34690.6735
1.30022.867012501.30420.6521
1.28593.440415001.29550.6478
1.24764.013817501.26760.6338
1.24224.587220001.27430.6371
1.19865.160622501.27910.6396
1.18515.733925001.25080.6254
1.19856.307327501.27400.6370
1.16686.880730001.25330.6267
1.14497.454132501.24080.6204
1.15008.027535001.24530.6227
1.13718.600937501.23910.6195
1.13259.174340001.25200.6260
1.10889.747742501.24720.6236

Framework versions

  • —PEFT 0.18.1
  • —Transformers 5.0.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 4.8.3
  • —Tokenizers 0.22.2