Updated docs

README.md

@@ -120,7 +120,7 @@ For advanced usage, please refer to our [usage documentation](https://github.com
 
 ## Updates & Announcements
 
-- **12/02/2024**: We released **Model2Vec training**, allowing you to fine-tune your own classification models on top of Model2Vec models. Find out more in our [training documentation](https://github.com/MinishLab/model2vec/blob/main/model2vec/train/README.md) and [results](https://github.com/MinishLab/blob/main/results#training-results).
+- **12/02/2024**: We released **Model2Vec training**, allowing you to fine-tune your own classification models on top of Model2Vec models. Find out more in our [training documentation](https://github.com/MinishLab/model2vec/blob/main/model2vec/train/README.md) and [results](results/README.md#training-results).
 
 - **30/01/2024**: We released two new models: [potion-base-32M](https://huggingface.co/minishlab/potion-base-32M) and [potion-retrieval-32M](https://huggingface.co/minishlab/potion-retrieval-32M). [potion-base-32M](https://huggingface.co/minishlab/potion-base-32M) is our most performant model to date, using a larger vocabulary and higher dimensions. [potion-retrieval-32M](https://huggingface.co/minishlab/potion-retrieval-32M) is a finetune of [potion-base-32M](https://huggingface.co/minishlab/potion-base-32M) that is optimized for retrieval tasks, and is the best performing static retrieval model currently available.
 
@@ -174,6 +174,7 @@ We provide a number of models that can be used out of the box. These models are
 
 We have performed extensive experiments to evaluate the performance of Model2Vec models. The results are documented in the [results](results/README.md) folder. The results are presented in the following sections:
 - [MTEB Results](results/README.md#mteb-results)
+- [Training Results](results/README.md#training-results)
 - [Ablations](results/README.md#ablations)
 
 ## License