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BERT-fully-trained-accuracy

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metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - gokuls/wiki_book_corpus_complete_processed_bert_dataset
model-index:
  - name: BERT-fully-trained-accuracy
    results: []

BERT-fully-trained-accuracy

This model is a fine-tuned version of bert-base-uncased on the gokuls/wiki_book_corpus_complete_processed_bert_dataset dataset. It achieves the following results on the evaluation set:

  • eval_loss: 2.3870
  • eval_accuracy: 0.5781
  • eval_runtime: 2139.188
  • eval_samples_per_second: 144.146
  • eval_steps_per_second: 4.505
  • step: 0

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: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 10
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10000
  • num_epochs: 5

Framework versions

  • Transformers 4.35.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.14.6
  • Tokenizers 0.14.1