---
license: mit
base_model: gpt2-medium
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: gpt2-medium-supervised-summarize-checkpoint
  results: []
---

<!-- 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-medium-supervised-summarize-checkpoint

This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7422
- Rouge1: 0.6035
- Rouge2: 0.2047
- Rougel: 0.4141
- Rougelsum: 0.5319

## 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: 1e-05
- train_batch_size: 50
- eval_batch_size: 50
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.859         | 0.21  | 500  | 1.8105          | 0.5966 | 0.1961 | 0.4025 | 0.5237    |
| 1.852         | 0.43  | 1000 | 1.7900          | 0.5994 | 0.1981 | 0.4061 | 0.5271    |
| 1.8189        | 0.64  | 1500 | 1.7764          | 0.6000 | 0.2005 | 0.4082 | 0.5276    |
| 1.8191        | 0.86  | 2000 | 1.7695          | 0.6013 | 0.2009 | 0.4096 | 0.5290    |
| 1.7969        | 1.07  | 2500 | 1.7617          | 0.6038 | 0.2020 | 0.4108 | 0.5311    |
| 1.7967        | 1.28  | 3000 | 1.7578          | 0.6024 | 0.2024 | 0.4114 | 0.5304    |
| 1.7813        | 1.5   | 3500 | 1.7520          | 0.6038 | 0.2039 | 0.4128 | 0.5320    |
| 1.7704        | 1.71  | 4000 | 1.7480          | 0.6033 | 0.2045 | 0.4132 | 0.5310    |
| 1.7852        | 1.93  | 4500 | 1.7422          | 0.6035 | 0.2047 | 0.4141 | 0.5319    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0