---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gpt2_summarization_reward_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gpt2_summarization_reward_model

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7263
- Accuracy: 0.6139

## 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
- distributed_type: multi-GPU
- num_devices: 16
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6323        | 1.0   | 1451 | 0.6663          | 0.6151   |
| 0.5834        | 2.0   | 2902 | 0.6736          | 0.6166   |
| 0.5443        | 3.0   | 4353 | 0.6831          | 0.6138   |
| 0.5141        | 4.0   | 5804 | 0.7137          | 0.6144   |
| 0.4971        | 5.0   | 7255 | 0.7263          | 0.6139   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2