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README.md

@@ -85,14 +85,14 @@ The model was trained with the parameters:
 
 **DataLoader**:
 
-`torch.utils.data.dataloader.DataLoader` of length 480 with parameters:
+`torch.utils.data.dataloader.DataLoader` of length 9677 with parameters:
 ```
 {'batch_size': 128, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
 ```
 
 **Loss**:
 
-`sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters:
+`__main__.LoggingMNRLoss` with parameters:
   ```
   {'scale': 20.0, 'similarity_fct': 'cos_sim'}
   ```
@@ -100,13 +100,13 @@ The model was trained with the parameters:
 Parameters of the fit()-Method:
 ```
 {
-    "epochs": 4,
+    "epochs": 2,
     "evaluation_steps": 0,
     "evaluator": "NoneType",
     "max_grad_norm": 1,
     "optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
     "optimizer_params": {
-        "lr": 0.0005
+        "lr": 5e-05
     },
     "scheduler": "WarmupLinear",
     "steps_per_epoch": null,
@@ -119,7 +119,7 @@ Parameters of the fit()-Method:
 ## Full Model Architecture
 ```
 SentenceTransformer(
-  (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel 
+  (0): Transformer({'max_seq_length': 80, '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 sha256:83127159d799535b99b7e43197dd8aec99d05acae6c0f553811c761a61b7c2f8
+oid sha256:f9f59ceb4c5ed27d084475090eab5ae6326986828725714247f7463538e45d7c
 size 46223689

sentence_bert_config.json

@@ -1,4 +1,4 @@
 {
-  "max_seq_length": 128,
+  "max_seq_length": 80,
   "do_lower_case": false
 }

tokenizer.json

@@ -2,7 +2,7 @@
   "version": "1.0",
   "truncation": {
     "direction": "Right",
-    "max_length": 128,
+    "max_length": 80,
     "strategy": "LongestFirst",
     "stride": 0
   },