---
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: 0.6912
- Accuracy: 0.57

## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.57  | 1    | 0.6911          | 0.58     |
| No log        | 1.57  | 2    | 0.6912          | 0.57     |
| No log        | 2.57  | 3    | 0.6912          | 0.57     |
| No log        | 3.57  | 4    | 0.6912          | 0.57     |
| No log        | 4.57  | 5    | 0.6912          | 0.57     |


### Framework versions

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