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README.md

@@ -85,7 +85,7 @@ The model was trained with the parameters:
 
 **DataLoader**:
 
-`torch.utils.data.dataloader.DataLoader` of length 4465 with parameters:
+`torch.utils.data.dataloader.DataLoader` of length 103 with parameters:
 ```
 {'batch_size': 224, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
 ```
@@ -119,7 +119,7 @@ Parameters of the fit()-Method:
 ## Full Model Architecture
 ```
 SentenceTransformer(
-  (0): Transformer({'max_seq_length': 150, 'do_lower_case': False}) with Transformer model: BertModel 
+  (0): Transformer({'max_seq_length': 60, 'do_lower_case': False}) with Transformer model: BertModel 
   (1): Pooling({'word_embedding_dimension': 256, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
 )
 ```

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:74f0e9ceb52730d9951a8722103938c7e1a9c494ee85ac0f462060cac3e1a394
+oid sha256:4e4bca2f6b31aa84e9baabdabdfba3cebbe7d603dc36ee1430a6d6ae7a7a6d9c
 size 46223689

sentence_bert_config.json

@@ -1,4 +1,4 @@
 {
-  "max_seq_length": 150,
+  "max_seq_length": 60,
   "do_lower_case": false
 }

tokenizer.json

@@ -2,7 +2,7 @@
   "version": "1.0",
   "truncation": {
     "direction": "Right",
-    "max_length": 150,
+    "max_length": 60,
     "strategy": "LongestFirst",
     "stride": 0
   },