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End of training
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metadata
library_name: transformers
tags:
  - generated_from_trainer
datasets:
  - Hartunka/processed_wikitext-103-raw-v1-rand-20_v2
metrics:
  - accuracy
model-index:
  - name: bert_base_rand_20_v1
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask
        dataset:
          name: Hartunka/processed_wikitext-103-raw-v1-rand-20_v2
          type: Hartunka/processed_wikitext-103-raw-v1-rand-20_v2
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.15341583319206645

bert_base_rand_20_v1

This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-rand-20_v2 dataset. It achieves the following results on the evaluation set:

  • Loss: 9.0827
  • Accuracy: 0.1534

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
  • train_batch_size: 96
  • eval_batch_size: 96
  • seed: 10
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10000
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy
9.059 4.1982 10000 9.0637 0.1508
8.3813 8.3963 20000 9.4918 0.1522
7.3399 12.5945 30000 10.8730 0.1537
6.6933 16.7926 40000 11.6926 0.1512
6.3773 20.9908 50000 12.3375 0.1518

Framework versions

  • Transformers 4.50.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.21.1