---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: superglue_rte-bert-base-uncased
  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: 0.6739130434782609
---

<!-- 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-bert-base-uncased

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the super_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5070
- Accuracy: 0.6739

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.704         | 1.0   | 623   | 0.6653          | 0.6159   |
| 0.6848        | 2.0   | 1246  | 0.7144          | 0.4203   |
| 0.7083        | 3.0   | 1869  | 0.6922          | 0.5797   |
| 0.7014        | 4.0   | 2492  | 0.7327          | 0.6232   |
| 0.6528        | 5.0   | 3115  | 0.6727          | 0.6522   |
| 0.6471        | 6.0   | 3738  | 0.8413          | 0.6159   |
| 0.5872        | 7.0   | 4361  | 0.8780          | 0.5507   |
| 0.5954        | 8.0   | 4984  | 0.7604          | 0.6377   |
| 0.5566        | 9.0   | 5607  | 0.8578          | 0.6812   |
| 0.5576        | 10.0  | 6230  | 2.0498          | 0.5362   |
| 0.4923        | 11.0  | 6853  | 1.4097          | 0.6304   |
| 0.5688        | 12.0  | 7476  | 1.4146          | 0.6667   |
| 0.433         | 13.0  | 8099  | 1.3354          | 0.6594   |
| 0.4259        | 14.0  | 8722  | 1.3271          | 0.6957   |
| 0.3869        | 15.0  | 9345  | 1.2881          | 0.6812   |
| 0.3641        | 16.0  | 9968  | 1.4485          | 0.6739   |
| 0.3292        | 17.0  | 10591 | 1.3445          | 0.6739   |
| 0.3734        | 18.0  | 11214 | 1.4917          | 0.6739   |
| 0.3227        | 19.0  | 11837 | 1.5281          | 0.6739   |
| 0.3133        | 20.0  | 12460 | 1.5070          | 0.6739   |


### Framework versions

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