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metadata
library_name: transformers
language:
  - en
base_model: gokulsrinivasagan/distilbert_lda_50_v1
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: distilbert_lda_50_v1_mnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MNLI
          type: glue
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.3295362082994304

distilbert_lda_50_v1_mnli

This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_50_v1 on the GLUE MNLI dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0962
  • Accuracy: 0.3295

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
1.1024 1.0 1534 1.0993 0.3274
1.0986 2.0 3068 1.0987 0.3545
1.0987 3.0 4602 1.0989 0.3274
1.0986 4.0 6136 1.1016 0.3182
1.0985 5.0 7670 1.0989 0.3545
1.0987 6.0 9204 1.0989 0.3545
1.0985 7.0 10738 1.0968 0.3182
1.0986 8.0 12272 1.0991 0.3182
1.0988 9.0 13806 1.0962 0.3274
1.0986 10.0 15340 1.0992 0.3274
1.0986 11.0 16874 1.0990 0.3274
1.0984 12.0 18408 1.0991 0.3182
1.0985 13.0 19942 1.0965 0.3182
1.0988 14.0 21476 1.0987 0.3274

Framework versions

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