---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gpt2-xl-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-xl-summarization_reward_model

This model is a fine-tuned version of [gpt2-xl](https://huggingface.co/gpt2-xl) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2875
- Accuracy: 0.6157

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5856        | 1.0   | 1451 | 0.6854          | 0.6218   |
| 0.4314        | 2.0   | 2902 | 0.8053          | 0.6133   |
| 0.3166        | 3.0   | 4353 | 0.8060          | 0.6146   |
| 0.2625        | 4.0   | 5804 | 0.9857          | 0.6162   |
| 0.2279        | 5.0   | 7255 | 1.2875          | 0.6157   |


### Framework versions

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