---
license: mit
base_model: openai-community/gpt2-large
tags:
- generated_from_trainer
datasets:
- stanfordnlp/snli
metrics:
- accuracy
model-index:
- name: gpt2-large-bn-adapter-7.42M-snli-model2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: snli
      type: stanfordnlp/snli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9006299532615322
---

<!-- 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. -->

# gpt2-large-bn-adapter-7.42M-snli-model2

This model is a fine-tuned version of [openai-community/gpt2-large](https://huggingface.co/openai-community/gpt2-large) on the snli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2734
- Accuracy: 0.9006

## 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: 32
- eval_batch_size: 32
- seed: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.374         | 1.0   | 17168 | 0.2993          | 0.8888   |
| 0.334         | 2.0   | 34336 | 0.2791          | 0.8989   |
| 0.307         | 3.0   | 51504 | 0.2734          | 0.9006   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0