Update README.md

README.md

@@ -12,15 +12,24 @@ should probably proofread and complete it, then remove this comment. -->
 
 # deep-haiku-gpt-2
 
-This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
+This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the [haiku](https://huggingface.co/datasets/statworx/haiku) dataset.
 
 ## Model description
 
-More information needed
+The model is a fine-tuned version of GPT-2 for generation of [Haikus](https://en.wikipedia.org/wiki/Haiku). The model, data and training procedure is inspired by a [blog post by Robert A. Gonsalves](https://towardsdatascience.com/deep-haiku-teaching-gpt-j-to-compose-with-syllable-patterns-5234bca9701). Instead of using a 8bit version of GPT-J 6B, we instead used vanilla GPT-2. From what we saw, the model performance comparable but is much easier to fine-tune.
+
+We used the same multitask training approach as in der post, but significantly extended the dataset (almost double the size of the original on). A prepared version of the dataset can be found [here](https://huggingface.co/datasets/statworx/haiku). 
 
 ## Intended uses & limitations
 
-More information needed
+The model is intended to generate Haikus. To do so, it was trained using a multitask learning approach (see [Caruana 1997](http://www.cs.cornell.edu/~caruana/mlj97.pdf)) with the following four different tasks: :
+
+ - topic2graphemes       `(keywords = text)`
+ - topic2phonemes        `<keyword_phonemes = text_phonemes>`
+ - graphemes2pphonemes   `[text = text_phonemes]`
+ - phonemes2graphemes    `{text_phonemes = text}`
+ 
+ To use the model, use an appropriate prompt like `(dog rain =` and let the model generate a Haiku given the keyword.
 
 ## Training and evaluation data