---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: superglue_rte-gpt2
  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: 0.5434782608695652
---

<!-- 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-gpt2

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the super_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4821
- Accuracy: 0.5435

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.778         | 1.0   | 623   | 0.6845          | 0.5797   |
| 0.7042        | 2.0   | 1246  | 0.6909          | 0.5797   |
| 0.7022        | 3.0   | 1869  | 0.6608          | 0.5507   |
| 0.7145        | 4.0   | 2492  | 0.7206          | 0.5797   |
| 0.6183        | 5.0   | 3115  | 0.8510          | 0.5435   |
| 0.5855        | 6.0   | 3738  | 1.7010          | 0.5362   |
| 0.5468        | 7.0   | 4361  | 2.3186          | 0.5362   |
| 0.4411        | 8.0   | 4984  | 2.6790          | 0.5435   |
| 0.3226        | 9.0   | 5607  | 2.6486          | 0.5507   |
| 0.2479        | 10.0  | 6230  | 3.2958          | 0.5362   |
| 0.1632        | 11.0  | 6853  | 3.3893          | 0.5290   |
| 0.1526        | 12.0  | 7476  | 3.2382          | 0.5942   |
| 0.1127        | 13.0  | 8099  | 4.0889          | 0.4855   |
| 0.0902        | 14.0  | 8722  | 3.7049          | 0.5580   |
| 0.0997        | 15.0  | 9345  | 3.6377          | 0.5290   |
| 0.083         | 16.0  | 9968  | 3.6723          | 0.6087   |
| 0.0612        | 17.0  | 10591 | 4.2905          | 0.5870   |
| 0.0357        | 18.0  | 11214 | 4.4611          | 0.5145   |
| 0.0643        | 19.0  | 11837 | 4.4033          | 0.5217   |
| 0.0348        | 20.0  | 12460 | 4.4821          | 0.5435   |


### Framework versions

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