mateiaass / albert-base-qa-2-k-fold-3

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Total runs: 10
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7-day runs: 1
30-day runs: 5
Model's Last Updated: October 25 2023
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Introduction of albert-base-qa-2-k-fold-3

Model Details of albert-base-qa-2-k-fold-3

albert-base-qa-2-k-fold-3

This model is a fine-tuned version of albert-base-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9272
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
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
Training results
Training Loss Epoch Step Validation Loss
0.9171 1.0 4602 0.8640
0.6699 2.0 9204 0.8303
0.4832 3.0 13806 0.9272
Framework versions
  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1

Runs of mateiaass albert-base-qa-2-k-fold-3 on huggingface.co

10
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3-day runs
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30-day runs

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