upload model

README.md

@@ -21,6 +21,12 @@ This model was adapted from [ytu-ce-cosmos/turkish-mini-bert-uncased](https://hu
 - [nli_tr](https://huggingface.co/datasets/nli_tr)
 - [emrecan/stsb-mt-turkish](https://huggingface.co/datasets/emrecan/stsb-mt-turkish)
 
+:warning: **All texts were manually lowercased,** [as stated](https://huggingface.co/ytu-ce-cosmos/turkish-tiny-bert-uncased#%E2%9A%A0-uncased-use-requires-manual-lowercase-conversion) by the model's authors:
+
+ ```python
+text.replace("I", "ı").lower()
+```
+
 ## Usage (Sentence-Transformers)
 
 Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
@@ -85,10 +91,10 @@ print(sentence_embeddings)
 Achieved results on the [STS-b](https://huggingface.co/datasets/emrecan/stsb-mt-turkish) test split are given below:
 
 ```txt
-Cosine-Similarity :       Pearson: 0.7039 Spearman: 0.6850
-Manhattan-Distance:       Pearson: 0.6774 Spearman: 0.6740
-Euclidean-Distance:       Pearson: 0.6770 Spearman: 0.6731
-Dot-Product-Similarity:   Pearson: 0.6716 Spearman: 0.6559
+Cosine-Similarity :	    Pearson: 0.8117	Spearman: 0.8074
+Manhattan-Distance:	    Pearson: 0.8029	Spearman: 0.7972
+Euclidean-Distance:	    Pearson: 0.8028	Spearman: 0.7977
+Dot-Product-Similarity:	Pearson: 0.7563	Spearman: 0.7435
 ```
 
 
@@ -97,9 +103,9 @@ The model was trained with the parameters:
 
 **DataLoader**:
 
-`torch.utils.data.dataloader.DataLoader` of length 90 with parameters:
+`torch.utils.data.dataloader.DataLoader` of length 45 with parameters:
 ```
-{'batch_size': 64, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
+{'batch_size': 128, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
 ```
 
 **Loss**:
@@ -109,8 +115,8 @@ The model was trained with the parameters:
 Parameters of the fit()-Method:
 ```
 {
-    "epochs": 5,
-    "evaluation_steps": 45,
+    "epochs": 10,
+    "evaluation_steps": 4,
     "evaluator": "sentence_transformers.evaluation.EmbeddingSimilarityEvaluator.EmbeddingSimilarityEvaluator",
     "max_grad_norm": 1,
     "optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
@@ -128,7 +134,7 @@ Parameters of the fit()-Method:
 ## Full Model Architecture
 ```
 SentenceTransformer(
-  (0): Transformer({'max_seq_length': 75, 'do_lower_case': False}) with Transformer model: BertModel 
+  (0): Transformer({'max_seq_length': 256, '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})
 )
 ```

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "e5_b64_turkish_mini_bert_uncased-mean-nli\\",
+  "_name_or_path": "output/ytu_ce_cosmos-turkish_mini_bert_uncased-b128-e10-nli/",
   "architectures": [
     "BertModel"
   ],

config_sentence_transformers.json

@@ -2,6 +2,6 @@
   "__version__": {
     "sentence_transformers": "2.2.2",
     "transformers": "4.28.0",
-    "pytorch": "2.0.1+cu118"
+    "pytorch": "2.1.0+cu121"
   }
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a2fd81857a006e7c045e1716e3d4a92bd0783ee6f1cece36b63533498e09c376
-size 46223689
+oid sha256:7b8f1f189b3b2f879d341806d765e0856cf2869b1a1a76ab42c441fe86ac983b
+size 46224134

sentence_bert_config.json

@@ -1,4 +1,4 @@
 {
-  "max_seq_length": 75,
+  "max_seq_length": 256,
   "do_lower_case": false
 }

tokenizer.json

@@ -2,7 +2,7 @@
   "version": "1.0",
   "truncation": {
     "direction": "Right",
-    "max_length": 75,
+    "max_length": 256,
     "strategy": "LongestFirst",
     "stride": 0
   },