bert_base_km_50_v2 / README.md
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metadata
library_name: transformers
tags:
  - generated_from_trainer
datasets:
  - Hartunka/processed_wikitext-103-raw-v1-km-50_v2
metrics:
  - accuracy
model-index:
  - name: bert_base_km_50_v2
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask
        dataset:
          name: Hartunka/processed_wikitext-103-raw-v1-km-50_v2
          type: Hartunka/processed_wikitext-103-raw-v1-km-50_v2
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.15383963383624344

bert_base_km_50_v2

This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-km-50_v2 dataset. It achieves the following results on the evaluation set:

  • Loss: 6.8821
  • Accuracy: 0.1538

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
6.8758 4.1982 10000 6.9273 0.1497
6.4229 8.3963 20000 6.8691 0.1526
6.1843 12.5945 30000 6.9468 0.1552
6.0459 16.7926 40000 7.1213 0.1520
5.9642 20.9908 50000 7.0947 0.1527

Framework versions

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