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End of training
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metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - gokulsrinivasagan/processed_wikitext-103-raw-v1-ld
metrics:
  - accuracy
model-index:
  - name: tinybert_base_train_kd
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask
        dataset:
          name: gokulsrinivasagan/processed_wikitext-103-raw-v1-ld
          type: gokulsrinivasagan/processed_wikitext-103-raw-v1-ld
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5510538509351868

tinybert_base_train_kd

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

  • Loss: 62.6034
  • Accuracy: 0.5511

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
447.3158 4.1982 10000 428.8420 0.1658
151.7919 8.3963 20000 135.7859 0.4816
95.9257 12.5945 30000 84.8065 0.5308
78.7736 16.7926 40000 70.8755 0.5468
70.9704 20.9908 50000 63.0908 0.5510

Framework versions

  • Transformers 4.51.2
  • Pytorch 2.6.0+cu126
  • Datasets 3.5.0
  • Tokenizers 0.21.1