Update README.md

README.md

@@ -9,11 +9,19 @@ model-index:
 - name: misogynistic-statements-classification-model
   results: []
 widget:
-- text: "Las mujeres deben ser madres antes que nada"
-  example_title: "Machista"
-- text: "Las mujeres tienen el mismo potencial y habilidades para los negocios que los hombres"
-  example_title: "No machista"
-
+- text: Las mujeres deben ser madres antes que nada
+  example_title: Machista
+- text: >-
+    Las mujeres tienen el mismo potencial y habilidades para los negocios que
+    los hombres
+  example_title: No machista
+datasets:
+- glombardo/misogynistic-statements-classification
+language:
+- es
+output_data:
+- format: class
+- class_labels: ["Sexist", "Non-sexist"]
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -21,7 +29,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 # misogynistic-statements-classification-model
 
-This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the glombardo/misogynistic-statements-classification dataset.
+**Model that classifies text as sexist or non-sexist.**
+
+This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the [misogynistic-statements-classification dataset](https://huggingface.co/datasets/glombardo/misogynistic-statements-classification).
 It achieves the following results on the evaluation set:
 - Loss: 0.2493
 - Accuracy: 0.9524
@@ -60,4 +70,4 @@ The following hyperparameters were used during training:
 - Transformers 4.28.1
 - Pytorch 2.0.0+cu118
 - Datasets 2.12.0
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3