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update model card README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - wikitext
metrics:
  - accuracy
model-index:
  - name: distilbert_add_pre-training-dim-96
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask
        dataset:
          name: wikitext wikitext-103-raw-v1
          type: wikitext
          config: wikitext-103-raw-v1
          split: validation
          args: wikitext-103-raw-v1
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.14942141332434558

distilbert_add_pre-training-dim-96

This model is a fine-tuned version of distilbert-base-uncased on the wikitext wikitext-103-raw-v1 dataset. It achieves the following results on the evaluation set:

  • Loss: 6.6092
  • Accuracy: 0.1494

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: 5e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • 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: 100
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
14.685 1.0 3573 9.3922 0.1240
8.0255 2.0 7146 7.1510 0.1315
7.0152 3.0 10719 6.7861 0.1482
6.8127 4.0 14292 6.7053 0.1493
6.74 5.0 17865 6.6695 0.1474
6.7067 6.0 21438 6.6431 0.1491
6.6871 7.0 25011 6.6204 0.1483
6.6748 8.0 28584 6.6250 0.1473
6.6649 9.0 32157 6.6108 0.1486
6.6596 10.0 35730 6.6140 0.1497
6.6536 11.0 39303 6.6067 0.1493
6.6483 12.0 42876 6.6140 0.1489
6.6463 13.0 46449 6.6096 0.1484
6.6434 14.0 50022 6.5570 0.1526
6.6414 15.0 53595 6.5836 0.1526

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.9.0
  • Tokenizers 0.13.2