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metadata
library_name: transformers
language:
  - en
base_model: gokulsrinivasagan/distilbert_lda_5_v1
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: distilbert_lda_5_v1_qnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QNLI
          type: glue
          args: qnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5053999633900788

distilbert_lda_5_v1_qnli

This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_5_v1 on the GLUE QNLI dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6914
  • Accuracy: 0.5054

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: 0.001
  • train_batch_size: 256
  • eval_batch_size: 256
  • 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
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7218 1.0 410 0.6934 0.4946
0.6932 2.0 820 0.6935 0.4946
0.6932 3.0 1230 0.6933 0.5054
0.6931 4.0 1640 0.6933 0.5054
0.6932 5.0 2050 0.6934 0.4946
0.6932 6.0 2460 0.6933 0.5054
0.6931 7.0 2870 0.6914 0.5054
0.693 8.0 3280 0.6934 0.4946
0.6932 9.0 3690 0.6933 0.5054
0.6932 10.0 4100 0.6934 0.4946
0.6932 11.0 4510 0.6933 0.5054
0.6932 12.0 4920 0.6934 0.4946

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.2.1+cu118
  • Datasets 2.17.0
  • Tokenizers 0.20.3