gokuls / distilbert_sa_GLUE_Experiment_data_aug_rte_192

huggingface.co
Total runs: 11
24-hour runs: 0
7-day runs: -4
30-day runs: -7
Model's Last Updated: February 02 2023
text-classification

Introduction of distilbert_sa_GLUE_Experiment_data_aug_rte_192

Model Details of distilbert_sa_GLUE_Experiment_data_aug_rte_192

distilbert_sa_GLUE_Experiment_data_aug_rte_192

This model is a fine-tuned version of distilbert-base-uncased on the GLUE RTE dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8449
  • Accuracy: 0.5199
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
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.2938 1.0 568 1.8449 0.5199
0.0556 2.0 1136 2.3009 0.4946
0.0295 3.0 1704 2.6341 0.5018
0.0183 4.0 2272 3.0449 0.5235
0.0119 5.0 2840 3.1349 0.5162
0.0091 6.0 3408 3.4876 0.5343
Framework versions
  • Transformers 4.26.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.9.0
  • Tokenizers 0.13.2

Runs of gokuls distilbert_sa_GLUE_Experiment_data_aug_rte_192 on huggingface.co

11
Total runs
0
24-hour runs
1
3-day runs
-4
7-day runs
-7
30-day runs

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