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