---
base_model: uer/gpt2-chinese-cluecorpussmall
tags:
- generated_from_trainer
model-index:
- name: similar_question_generation
  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. -->

# similar_question_generation

This model is a fine-tuned version of [uer/gpt2-chinese-cluecorpussmall](https://huggingface.co/uer/gpt2-chinese-cluecorpussmall) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0045

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.2108        | 0.21  | 1000  | 2.0433          |
| 2.047         | 0.42  | 2000  | 2.0138          |
| 1.9859        | 0.63  | 3000  | 1.9939          |
| 1.9471        | 0.84  | 4000  | 1.9953          |
| 1.8932        | 1.05  | 5000  | 2.0034          |
| 1.8224        | 1.26  | 6000  | 1.9962          |
| 1.8131        | 1.47  | 7000  | 1.9886          |
| 1.8007        | 1.69  | 8000  | 1.9881          |
| 1.7948        | 1.9   | 9000  | 1.9825          |
| 1.7314        | 2.11  | 10000 | 2.0049          |
| 1.6901        | 2.32  | 11000 | 2.0029          |
| 1.6941        | 2.53  | 12000 | 2.0012          |
| 1.6921        | 2.74  | 13000 | 2.0024          |
| 1.6917        | 2.95  | 14000 | 2.0045          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0