Update README.md

README.md

@@ -1,36 +1,35 @@
----
-library_name: transformers
-license: mit
-base_model: microsoft/MiniLM-L12-H384-uncased
-tags:
-- generated_from_trainer
-model-index:
-- name: bert-mini-squadv2
-  results: []
----
+---
+library_name: transformers
+license: mit
+base_model: microsoft/MiniLM-L12-H384-uncased
+tags:
+- generated_from_trainer
+- extractive_QA
+model-index:
+- name: bert-mini-squadv2
+  results: []
+datasets:
+- hf-tuner/squad_v2.0.1
+language:
+- en
+metrics:
+- exact_match
+pipeline_tag: question-answering
+---
 
 <!-- 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-mini-squadv2
 
-This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on an unknown dataset.
+This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on 
+[hf-tuner/squad_v2.0.1](https://huggingface.co/datasets/hf-tuner/squad_v2.0.1) dataset.
 It achieves the following results on the evaluation set:
 - Loss: 1.4653
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
+MiniLMv1-L12-H384-uncased: 12-layer, 384-hidden, 12-heads, 33M parameters, 2.7x faster than BERT-Base
 
 ### Training hyperparameters
 
@@ -57,4 +56,4 @@ The following hyperparameters were used during training:
 - Transformers 4.57.1
 - Pytorch 2.8.0+cu126
 - Datasets 4.0.0
-- Tokenizers 0.22.1
+- Tokenizers 0.22.1