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---
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
---
<!-- 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: 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
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