
## Model Details
GPT-2 Pretrained on Wikitext-103 (180M sentences) on 32GB V100 GPU for around 1.10L iterations. 

Val_loss vs train_loss:
![Loss curve](https://huggingface.co/himanshubeniwal/gpt2-wikitext103/resolve/main/sample.png)


### Model Description

Perplexity: 22.87


### Out-of-Scope Use

Just a test model. Please don't expect good results.


{"language": ["en"], "datasets": ["wikitext"], "metrics": ["perplexity"]}
transformers pytorch gpt2 text-generation en dataset:wikitext autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #en #dataset-wikitext #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


## Model Details
GPT-2 Pretrained on Wikitext-103 (180M sentences) on 32GB V100 GPU for around 1.10L iterations. 

Val_loss vs train_loss:
!Loss curve


### Model Description

Perplexity: 22.87


### Out-of-Scope Use

Just a test model. Please don't expect good results.


## Model Details
GPT-2 Pretrained on Wikitext-103 (180M sentences) on 32GB V100 GPU for around 1.10L iterations. 

Val_loss vs train_loss:
!Loss curve ### Model Description

Perplexity: 22.87 ### Out-of-Scope Use

Just a test model. Please don't expect good results.
TAGS
#transformers #pytorch #gpt2 #text-generation #en #dataset-wikitext #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ## Model Details
GPT-2 Pretrained on Wikitext-103 (180M sentences) on 32GB V100 GPU for around 1.10L iterations. 

Val_loss vs train_loss:
!Loss curve ### Model Description

Perplexity: 22.87 ### Out-of-Scope Use

Just a test model. Please don't expect good results.
TAGS
#transformers #pytorch #gpt2 #text-generation #en #dataset-wikitext #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
## Model Details
GPT-2 Pretrained on Wikitext-103 (180M sentences) on 32GB V100 GPU for around 1.10L iterations. 

Val_loss vs train_loss:
!Loss curve### Model Description

Perplexity: 22.87### Out-of-Scope Use

Just a test model. Please don't expect good results.