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metadata
library_name: transformers
language:
  - en
base_model: gokulsrinivasagan/distilbert_lda_100_v1_book
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: distilbert_lda_100_v1_book_rte
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE RTE
          type: glue
          args: rte
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5270758122743683

distilbert_lda_100_v1_book_rte

This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_100_v1_book on the GLUE RTE dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6902
  • Accuracy: 0.5271

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: 256
  • eval_batch_size: 256
  • seed: 10
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7006 1.0 10 0.6935 0.4765
0.6908 2.0 20 0.6908 0.5199
0.6809 3.0 30 0.6902 0.5271
0.6542 4.0 40 0.6959 0.5343
0.5813 5.0 50 0.7287 0.5560
0.4761 6.0 60 0.7502 0.5632
0.3513 7.0 70 0.8904 0.5776
0.2219 8.0 80 1.1421 0.5415

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.2.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.1