pytorch generated_from_trainer license:mit region:us
---
license: mit
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: gpt2-summarization_reward_model
  results: []
---

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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: 0.7473
- Accuracy: 0.6006

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6421        | 1.0   | 1451 | 0.6815          | 0.6036   |
| 0.5893        | 2.0   | 2902 | 0.6764          | 0.6048   |
| 0.5488        | 3.0   | 4353 | 0.7074          | 0.6012   |
| 0.5187        | 4.0   | 5804 | 0.7254          | 0.6009   |
| 0.5034        | 5.0   | 7255 | 0.7473          | 0.6006   |


### Framework versions

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