Update README.md

README.md

@@ -17,27 +17,30 @@ should probably proofread and complete it, then remove this comment. -->
 
 # finetuning
 
-This model is a fine-tuned version of [allegro/herbert-base-cased](https://huggingface.co/allegro/herbert-base-cased) on an unknown dataset.
+This model is a fine-tuned version of [allegro/herbert-base-cased](https://huggingface.co/allegro/herbert-base-cased) on a [jziebura/polish_youth_slang_classification](https://huggingface.co/datasets/jziebura/polish_youth_slang_classification) dataset.
+
 It achieves the following results on the evaluation set:
 - Loss: 0.7289
 - Accuracy: 0.7127
-- F1: 0.7110
+- F1 weighted: 0.7110
 - F1 Macro: 0.6977
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
+The model is part of the experiments conducted during the creation of my master's thesis titled: *"A language model analyzing Polish youth slang"*. 
 
-More information needed
+It was fine-tuned to classify the sentiment of the Polish youth slang into three categories: negative, neutral or ambiguous, and positive.
 
 ## Training and evaluation data
 
-More information needed
+All data comes from the [jziebura/polish_youth_slang_classification](https://huggingface.co/datasets/jziebura/polish_youth_slang_classification) dataset
 
 ## Training procedure
 
+The hyperparameters were selected from those recommended in the [BERT introduction paper](https://arxiv.org/abs/1810.04805) and then optimized using the Optuna backend.
+
+The HPO and fine-tuning were both conducted on the Google Colab platform on their free-tier T4 GPU instances.
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training: