---
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: 0.631768953068592
---

<!-- 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: 3.9334
- Accuracy: 0.6318

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6845        | 1.0   | 623   | 0.6880          | 0.5379   |
| 0.6015        | 2.0   | 1246  | 0.8206          | 0.6426   |
| 0.5012        | 3.0   | 1869  | 1.4769          | 0.6354   |
| 0.4173        | 4.0   | 2492  | 1.7735          | 0.6570   |
| 0.078         | 5.0   | 3115  | 2.2116          | 0.6354   |
| 0.0732        | 6.0   | 3738  | 2.6033          | 0.6318   |
| 0.0703        | 7.0   | 4361  | 2.7944          | 0.6390   |
| 0.0543        | 8.0   | 4984  | 2.6007          | 0.6462   |
| 0.0505        | 9.0   | 5607  | 2.4168          | 0.6462   |
| 0.0412        | 10.0  | 6230  | 2.7503          | 0.6787   |
| 0.0303        | 11.0  | 6853  | 3.2166          | 0.6643   |
| 0.0214        | 12.0  | 7476  | 3.0135          | 0.6498   |
| 0.0416        | 13.0  | 8099  | 2.9919          | 0.6534   |
| 0.0252        | 14.0  | 8722  | 3.0985          | 0.6570   |
| 0.0122        | 15.0  | 9345  | 3.5950          | 0.6209   |
| 0.009         | 16.0  | 9968  | 3.5463          | 0.6354   |
| 0.0034        | 17.0  | 10591 | 3.6333          | 0.6570   |
| 0.0109        | 18.0  | 11214 | 3.6860          | 0.6426   |
| 0.0041        | 19.0  | 11837 | 3.9160          | 0.6354   |
| 0.0           | 20.0  | 12460 | 3.9334          | 0.6318   |


### Framework versions

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