Update README.md

README.md

@@ -7,28 +7,22 @@ tags:
 model-index:
 - name: bert-philosophy-adapted
   results: []
+datasets:
+- AiresPucrs/stanford-encyclopedia-philosophy
+language:
+- en
+pipeline_tag: text-classification
 ---
 
-<!-- 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. -->
-
 # bert-philosophy-adapted
 
-This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [Standford Encylcopedia of Philosophy](https://huggingface.co/datasets/AiresPucrs/stanford-encyclopedia-philosophy) dataset, using masked language modeling.
 It achieves the following results on the evaluation set:
 - Loss: 1.5044
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
+This model was trained with the intention of creating a BERT encoder model for philosophical terminology, and further training on downstream tasks such as school of philosophy text classification.
 
 ## Training procedure
 
@@ -87,4 +81,4 @@ The following hyperparameters were used during training:
 - Transformers 4.52.4
 - Pytorch 2.6.0+cu124
 - Datasets 3.6.0
-- Tokenizers 0.21.1
+- Tokenizers 0.21.1