---
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: 0.7725631768953068
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# superglue_rte-t5-base

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the super_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5687
- Accuracy: 0.7726

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7109        | 1.0   | 623   | 0.6765          | 0.5740   |
| 0.6562        | 2.0   | 1246  | 0.6030          | 0.6968   |
| 0.548         | 3.0   | 1869  | 0.8049          | 0.7617   |
| 0.4129        | 4.0   | 2492  | 1.3536          | 0.7329   |
| 0.2189        | 5.0   | 3115  | 1.3886          | 0.7834   |
| 0.1378        | 6.0   | 3738  | 1.7001          | 0.7690   |
| 0.0905        | 7.0   | 4361  | 2.0587          | 0.7545   |
| 0.0434        | 8.0   | 4984  | 2.1796          | 0.7798   |
| 0.0715        | 9.0   | 5607  | 1.9936          | 0.7978   |
| 0.0616        | 10.0  | 6230  | 1.9794          | 0.7762   |
| 0.0609        | 11.0  | 6853  | 2.5575          | 0.7509   |
| 0.0108        | 12.0  | 7476  | 2.1022          | 0.7834   |
| 0.0142        | 13.0  | 8099  | 2.0628          | 0.7834   |
| 0.03          | 14.0  | 8722  | 2.1540          | 0.7726   |
| 0.0163        | 15.0  | 9345  | 2.3830          | 0.7653   |
| 0.0152        | 16.0  | 9968  | 2.5031          | 0.7617   |
| 0.0092        | 17.0  | 10591 | 2.4850          | 0.7653   |
| 0.0069        | 18.0  | 11214 | 2.4939          | 0.7726   |
| 0.0184        | 19.0  | 11837 | 2.4949          | 0.7690   |
| 0.0204        | 20.0  | 12460 | 2.5687          | 0.7726   |


### Framework versions

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