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# Wenzhong-GPT2-110M-THUCNews

This model is a fine-tuned version of [IDEA-CCNL/Wenzhong-GPT2-110M](https://huggingface.co/IDEA-CCNL/Wenzhong-GPT2-110M) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2403

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.295         | 1.0   | 2500  | 1.1898          |
| 1.1713        | 2.0   | 5000  | 1.1759          |
| 1.1218        | 3.0   | 7500  | 1.1765          |
| 1.0846        | 4.0   | 10000 | 1.1780          |
| 1.0536        | 5.0   | 12500 | 1.1840          |
| 1.0264        | 6.0   | 15000 | 1.1904          |
| 1.0025        | 7.0   | 17500 | 1.1969          |
| 0.9812        | 8.0   | 20000 | 1.2026          |
| 0.9623        | 9.0   | 22500 | 1.2091          |
| 0.9458        | 10.0  | 25000 | 1.2167          |
| 0.9312        | 11.0  | 27500 | 1.2220          |
| 0.9181        | 12.0  | 30000 | 1.2292          |
| 0.9073        | 13.0  | 32500 | 1.2349          |
| 0.8985        | 14.0  | 35000 | 1.2382          |
| 0.8921        | 15.0  | 37500 | 1.2403          |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "Wenzhong-GPT2-110M-THUCNews", "results": []}]}
transformers pytorch tensorboard safetensors gpt2 text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

Wenzhong-GPT2-110M-THUCNews
===========================


This model is a fine-tuned version of IDEA-CCNL/Wenzhong-GPT2-110M on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.2403


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2