krishdebroy/reward-bert-full-sft

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reward-bert-full-sft

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

• —Loss: 0.0324

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: 16
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 5
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.45.2
• —Pytorch 2.8.0+cu126
• —Datasets 4.4.2
• —Tokenizers 0.20.3