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bert-gpqa
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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: results
    results: []

results

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2400
  • Accuracy: 0.8996

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: 0.001
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 28 1.3861 0.2679
No log 2.0 56 1.3857 0.2723
No log 3.0 84 1.3847 0.3304
No log 4.0 112 1.3618 0.5759
No log 5.0 140 0.8967 0.6763
No log 6.0 168 0.5932 0.7969
No log 7.0 196 0.4044 0.8638
No log 8.0 224 0.3016 0.9129
No log 9.0 252 0.3303 0.8772
No log 10.0 280 0.2400 0.8996

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2