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metadata
license: apache-2.0
base_model: t5-base
tags:
  - generated_from_trainer
datasets:
  - super_glue
metrics:
  - accuracy
model-index:
  - name: superglue_rte-t5-base
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: super_glue
          type: super_glue
          config: rte
          split: validation
          args: rte
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8405797101449275

superglue_rte-t5-base

This model is a fine-tuned version of t5-base on the super_glue dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8826
  • Accuracy: 0.8406

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: 4
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7037 1.0 623 0.6646 0.5797
0.6448 2.0 1246 0.5461 0.7899
0.4943 3.0 1869 0.8069 0.7536
0.3854 4.0 2492 1.2553 0.8188
0.1244 5.0 3115 1.4887 0.7826
0.0836 6.0 3738 1.7422 0.7681
0.0672 7.0 4361 1.7002 0.8116
0.0449 8.0 4984 1.9237 0.7971
0.0246 9.0 5607 1.7064 0.7899
0.0239 10.0 6230 1.4433 0.8551
0.0233 11.0 6853 2.1623 0.7754
0.0348 12.0 7476 2.2059 0.7754
0.0268 13.0 8099 1.9322 0.8261
0.0076 14.0 8722 2.5687 0.7464
0.0117 15.0 9345 2.3024 0.7899
0.0129 16.0 9968 2.0848 0.7971
0.0206 17.0 10591 1.9453 0.8333
0.0162 18.0 11214 2.1232 0.7971
0.0132 19.0 11837 1.9754 0.8406
0.0098 20.0 12460 1.8826 0.8406

Framework versions

  • Transformers 4.32.1
  • Pytorch 1.13.0+cu117
  • Datasets 2.15.0
  • Tokenizers 0.13.3