transformers pytorch gpt2 text-classification generated_from_trainer dataset:wiki_qa base_model:openai-community/gpt2 base_model:finetune:openai-community/gpt2 license:mit model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: gpt2
datasets:
- wiki_qa
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: GPT2QA_wikiqa
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: wiki_qa
      type: wiki_qa
      config: default
      split: test
      args: default
    metrics:
    - type: accuracy
      value: 0.9578606158833063
      name: Accuracy
    - type: f1
      value: 0.0
      name: F1
---

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# GPT2QA_wikiqa

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the wiki_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2413
- Accuracy: 0.9579
- F1: 0.0

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|
| 0.1963        | 1.0   | 1387 | 0.2651          | 0.9579   | 0.0 |
| 0.2095        | 2.0   | 2774 | 0.2413          | 0.9579   | 0.0 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
