hyperparameter tuning step 19519

README.md

@@ -72,28 +72,28 @@ Coming soon!
 
 ## Eval results
 
-accuracy: 0.9163713678242381
 
-loss: 0.29771897196769714
+Loss: 0.2477145493030548
 
-macro_f1: 0.8951960933373831
+Accuracy: 0.926293408929837
 
-macro_precision: 0.8958313840463195
+Macro F1: 0.9079785326650756
 
-macro_recall: 0.8962088356299692
+Recall: 0.926293408929837
 
-micro_f1: 0.9163713678242381
+Weighted F1: 0.9266428029354202
 
-micro_precision: 0.9163713678242381
+Macro Precision: 0.9109938492260489
 
-micro_recall: 0.9163713678242381
+Micro Precision: 0.926293408929837
 
-weighted_f1: 0.916670480049282
+Weighted Precision: 0.9288535478995414
 
-weighted_precision: 0.9180146709071523
+Macro Recall: 0.9069095007692186
 
-weighted_recall: 0.9163713678242381
+Micro Recall: 0.926293408929837
 
+Weighted Recall: 0.926293408929837
 
 
 ### BibTeX entry and citation info

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "albertvillanova/autonlp-indic_glue-multi_class_classification-1e67664-1311135",
+  "_name_or_path": "albertvillanova/autonlp-baselines-indic_glue-multi_class_classification-1351187",
   "_num_labels": 6,
   "architectures": [
     "AlbertForSequenceClassification"
@@ -34,7 +34,7 @@
     "5": 5
   },
   "layer_norm_eps": 1e-12,
-  "max_length": 128,
+  "max_length": 64,
   "max_position_embeddings": 512,
   "model_type": "albert",
   "net_structure_type": 0,

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:d913b66b742f5a16df7ebc0993ed65fbd78d685433bb7bd9d99f5f3590e3e1fd
 size 71800235