CoolFace
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wenda2025/OBert

sourceHugging Faceupdated 5mo agoView on Hugging Face
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Model Card

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OBert

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.5998

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: 4
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 16
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 2000
  • —num_epochs: 251
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
6.537910.0452200000.9408
3.436020.0904400000.8064
2.947530.1357600000.7386
2.666640.1809800000.7093
2.473050.22611000000.6868
2.322960.27131200000.6716
2.203970.31651400000.6586
2.107580.36181600000.6550
2.019090.40701800000.6472
1.9435100.45222000000.6215
1.8781110.49742200000.6290
1.8177120.54262400000.6302
1.7646130.58792600000.6168
1.7101140.63312800000.6162
1.6629150.67833000000.5982
1.6214160.72353200000.5996
1.5817170.76873400000.6098
1.5453180.81403600000.5998

Framework versions

  • —Transformers 5.6.2
  • —Pytorch 2.11.0+cu130
  • —Datasets 4.8.4
  • —Tokenizers 0.22.2