transformers pytorch t5 text-classification generated_from_trainer dataset:super_glue base_model:google-t5/t5-base base_model:finetune:google-t5/t5-base license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-base
datasets:
- super_glue
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: superglue_rte-t5-base
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: super_glue
      type: super_glue
      config: rte
      split: validation
      args: rte
    metrics:
    - type: accuracy
      value: 0.8405797101449275
      name: Accuracy
---

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# 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: 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
