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

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: 0.5142

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 72.7331       | 0.03  | 10   | 64.5524         |
| 31.1386       | 0.06  | 20   | 18.0676         |
| 8.0161        | 0.08  | 30   | 6.4050          |
| 3.3753        | 0.11  | 40   | 2.7106          |
| 1.601         | 0.14  | 50   | 1.1822          |
| 0.9923        | 0.17  | 60   | 0.8619          |
| 1.0632        | 0.2   | 70   | 0.8305          |
| 0.7501        | 0.23  | 80   | 0.6396          |
| 0.6715        | 0.25  | 90   | 0.6099          |
| 0.5965        | 0.28  | 100  | 0.6137          |
| 0.711         | 0.31  | 110  | 0.5942          |
| 0.6546        | 0.34  | 120  | 0.5745          |
| 0.6075        | 0.37  | 130  | 0.5696          |
| 0.5607        | 0.4   | 140  | 0.5633          |
| 0.5469        | 0.42  | 150  | 0.5569          |
| 0.6887        | 0.45  | 160  | 0.5543          |
| 0.6184        | 0.48  | 170  | 0.5495          |
| 0.596         | 0.51  | 180  | 0.5474          |
| 0.6104        | 0.54  | 190  | 0.5442          |
| 0.5553        | 0.57  | 200  | 0.5388          |
| 0.5714        | 0.59  | 210  | 0.5346          |
| 0.534         | 0.62  | 220  | 0.5356          |
| 0.5739        | 0.65  | 230  | 0.5326          |
| 0.5873        | 0.68  | 240  | 0.5298          |
| 0.619         | 0.71  | 250  | 0.5312          |
| 0.6038        | 0.74  | 260  | 0.5282          |
| 0.6058        | 0.76  | 270  | 0.5241          |
| 0.5508        | 0.79  | 280  | 0.5252          |
| 0.5919        | 0.82  | 290  | 0.5233          |
| 0.6513        | 0.85  | 300  | 0.5206          |
| 0.6376        | 0.88  | 310  | 0.5178          |
| 0.6252        | 0.91  | 320  | 0.5181          |
| 0.5341        | 0.93  | 330  | 0.5160          |
| 0.5913        | 0.96  | 340  | 0.5139          |
| 0.6227        | 0.99  | 350  | 0.5143          |
| 0.4582        | 1.02  | 360  | 0.5140          |
| 0.5281        | 1.05  | 370  | 0.5142          |


### Framework versions

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