---
license: mit
tags:
- generated_from_trainer
model-index:
- name: gpt2-kl_01_04-hs_cn-loto_women
  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-kl_01_04-hs_cn-loto_women

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: 0.5255

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 21
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 72.3926       | 0.03  | 10   | 64.4148         |
| 30.9965       | 0.06  | 20   | 18.3281         |
| 9.3508        | 0.08  | 30   | 6.8328          |
| 3.4241        | 0.11  | 40   | 2.8584          |
| 1.6453        | 0.14  | 50   | 1.2170          |
| 1.2959        | 0.17  | 60   | 0.9385          |
| 0.8158        | 0.2   | 70   | 0.7754          |
| 0.6544        | 0.23  | 80   | 0.7423          |
| 0.6712        | 0.25  | 90   | 0.7252          |
| 0.699         | 0.28  | 100  | 0.6105          |
| 0.6505        | 0.31  | 110  | 0.5996          |
| 0.5894        | 0.34  | 120  | 0.6120          |
| 0.6332        | 0.37  | 130  | 0.5771          |
| 0.5938        | 0.4   | 140  | 0.5713          |
| 0.6967        | 0.42  | 150  | 0.5658          |
| 0.5814        | 0.45  | 160  | 0.5639          |
| 0.6871        | 0.48  | 170  | 0.5620          |
| 0.7062        | 0.51  | 180  | 0.5577          |
| 0.6324        | 0.54  | 190  | 0.5526          |
| 0.5662        | 0.57  | 200  | 0.5551          |
| 0.5518        | 0.59  | 210  | 0.5488          |
| 0.6076        | 0.62  | 220  | 0.5491          |
| 0.5995        | 0.65  | 230  | 0.5428          |
| 0.5814        | 0.68  | 240  | 0.5438          |
| 0.5011        | 0.71  | 250  | 0.5429          |
| 0.5419        | 0.74  | 260  | 0.5419          |
| 0.5354        | 0.76  | 270  | 0.5392          |
| 0.6176        | 0.79  | 280  | 0.5355          |
| 0.5353        | 0.82  | 290  | 0.5367          |
| 0.6365        | 0.85  | 300  | 0.5312          |
| 0.6529        | 0.88  | 310  | 0.5319          |
| 0.5899        | 0.91  | 320  | 0.5277          |
| 0.5617        | 0.93  | 330  | 0.5263          |
| 0.6409        | 0.96  | 340  | 0.5250          |
| 0.6277        | 0.99  | 350  | 0.5218          |
| 0.5406        | 1.02  | 360  | 0.5229          |
| 0.4896        | 1.05  | 370  | 0.5267          |
| 0.4776        | 1.08  | 380  | 0.5255          |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.11.0+cu113
- Datasets 2.11.0
- Tokenizers 0.13.3