Update README.md

README.md

@@ -41,12 +41,10 @@ We use the pretrained [`sentence-transformers/all-mpnet-base-v2`](https://huggin
 
  We use the initial model without modifying its architecture or pre-trained model parameters. 
  However, we reduce the processed sequence length to 384 to reduce the training time of the model. 
- Regarding other hyperparameters, we use the same interaction data batch size of 1024; we use the negative sampling parameter m = 10000.
- We use constant learning rate of 1e-5, and we train the model for five epochs.
 
 ### Dataset
   
- We finetuned our model on the Goodbooks-10k dataset with item descriptions generated with [`meta-llama/Meta-Llama-3.1-8B-Instruct`](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) model. For details please see the dataset page [`beeformer/recsys-movielens-20m`](https://huggingface.co/datasets/beeformer/recsys-movielens-20m).
+ We finetuned our model on the MovieLens-20M dataset with item descriptions generated with [`meta-llama/Meta-Llama-3.1-8B-Instruct`](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) model. For details please see the dataset page [`beeformer/recsys-movielens-20m`](https://huggingface.co/datasets/beeformer/recsys-movielens-20m).
 
 ## Evaluation Results