Update README model architecture

README.md

@@ -377,8 +377,8 @@ This is a [Asymmetric Inference-free SPLADE Sparse Encoder](https://www.sbert.ne
 ```
 SparseEncoder(
   (0): Router(
-    (query_0_IDF): IDF ({'frozen': False}, dim:30522, tokenizer: DistilBertTokenizerFast)
-    (document_0_MLMTransformer): MLMTransformer({'max_seq_length': 512, 'do_lower_case': False}) with MLMTransformer model: DistilBertForMaskedLM 
+    (query_0_SparseStaticEmbedding): SparseStaticEmbedding({'frozen': False}, dim:30522, tokenizer: DistilBertTokenizerFast)
+    (document_0_MLMTransformer): MLMTransformer({'max_seq_length': 512, 'do_lower_case': False, 'architecture': 'DistilBertForMaskedLM'})
     (document_1_SpladePooling): SpladePooling({'pooling_strategy': 'max', 'activation_function': 'relu', 'word_embedding_dimension': 30522})
   )
 )
@@ -591,7 +591,7 @@ You can finetune this model on your own dataset.
 - `fp16`: True
 - `batch_sampler`: no_duplicates
 - `router_mapping`: {'query': 'query', 'answer': 'document'}
-- `learning_rate_mapping`: {'IDF\\.weight': 0.001}
+- `learning_rate_mapping`: {'SparseStaticEmbedding\\.weight': 0.001}
 
 #### All Hyperparameters
 <details><summary>Click to expand</summary>
@@ -710,7 +710,7 @@ You can finetune this model on your own dataset.
 - `batch_sampler`: no_duplicates
 - `multi_dataset_batch_sampler`: proportional
 - `router_mapping`: {'query': 'query', 'answer': 'document'}
-- `learning_rate_mapping`: {'IDF\\.weight': 0.001}
+- `learning_rate_mapping`: {'SparseStaticEmbedding\\.weight': 0.001}
 
 </details>