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hyperparameter tuning step 19519

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  1. README.md +11 -11
  2. config.json +2 -2
  3. pytorch_model.bin +1 -1
README.md CHANGED
@@ -72,28 +72,28 @@ Coming soon!
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  ## Eval results
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- accuracy: 0.9163713678242381
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- loss: 0.29771897196769714
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- macro_f1: 0.8951960933373831
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- macro_precision: 0.8958313840463195
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- macro_recall: 0.8962088356299692
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- micro_f1: 0.9163713678242381
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- micro_precision: 0.9163713678242381
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- micro_recall: 0.9163713678242381
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- weighted_f1: 0.916670480049282
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- weighted_precision: 0.9180146709071523
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- weighted_recall: 0.9163713678242381
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  ### BibTeX entry and citation info
 
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  ## Eval results
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+ Loss: 0.2477145493030548
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+ Accuracy: 0.926293408929837
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+ Macro F1: 0.9079785326650756
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+ Recall: 0.926293408929837
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+ Weighted F1: 0.9266428029354202
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+ Macro Precision: 0.9109938492260489
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+ Micro Precision: 0.926293408929837
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+ Weighted Precision: 0.9288535478995414
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+ Macro Recall: 0.9069095007692186
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+ Micro Recall: 0.926293408929837
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+ Weighted Recall: 0.926293408929837
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  ### BibTeX entry and citation info
config.json CHANGED
@@ -1,5 +1,5 @@
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  {
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- "_name_or_path": "albertvillanova/autonlp-indic_glue-multi_class_classification-1e67664-1311135",
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  "_num_labels": 6,
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  "architectures": [
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  "AlbertForSequenceClassification"
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  "5": 5
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  },
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  "layer_norm_eps": 1e-12,
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- "max_length": 128,
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  "max_position_embeddings": 512,
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  "model_type": "albert",
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  "net_structure_type": 0,
 
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  {
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+ "_name_or_path": "albertvillanova/autonlp-baselines-indic_glue-multi_class_classification-1351187",
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  "_num_labels": 6,
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  "architectures": [
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  "AlbertForSequenceClassification"
 
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  "5": 5
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  },
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  "layer_norm_eps": 1e-12,
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+ "max_length": 64,
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  "max_position_embeddings": 512,
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  "model_type": "albert",
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  "net_structure_type": 0,
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
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