update model card

README.md

@@ -12,21 +12,22 @@ model-index:
 <!-- 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-finetuned-headliner
+# GPT2 Fine Tuned Headline Generator
 
-This model is a fine-tuned version of [openai-community/gpt2-medium](https://huggingface.co/openai-community/gpt2-medium) on an unknown dataset.
+- This model is trained on the [harvard/abcnews-dataset](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/SYBGZL) to generate news headlines
+- This model is a fine-tuned version of [openai-community/gpt2-medium](https://huggingface.co/openai-community/gpt2-medium) on an unknown dataset.
 
 ## Model description
 
-More information needed
+The model is fine-tuned for 2 epochs and 4k training samples from the abcnews dataset. This enables the model to generate news headline like text given a simple prompt
 
 ## Intended uses & limitations
 
-More information needed
+This model is only for learning purposes only. The model easily hallucinates people names, locations and other artifacts & incidents.
 
 ## Training and evaluation data
 
-More information needed
+The model leverages 2k test samples for evaluation
 
 ## Training procedure
 
@@ -43,7 +44,8 @@ The following hyperparameters were used during training:
 - num_epochs: 2
 
 ### Training results
-
+The final output after 2 epochs is as follows:
+TrainOutput(global_step=130, training_loss=5.044873604407678, metrics={'train_runtime': 140.587, 'train_samples_per_second': 59.166, 'train_steps_per_second': 0.925, 'total_flos': 248723096358912.0, 'train_loss': 5.044873604407678, 'epoch': 2.0})
 
 
 ### Framework versions