model update

README.md

@@ -113,10 +113,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.9240620762392647
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.9209428077000147
   - task:
       name: Lexical Relation Classification (CogALexV)
       type: classification
@@ -127,10 +127,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.8697183098591549
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.7120211843349907
   - task:
       name: Lexical Relation Classification (EVALution)
       type: classification
@@ -141,10 +141,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.7145178764897074
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.6950368132437731
   - task:
       name: Lexical Relation Classification (K&H+N)
       type: classification
@@ -155,10 +155,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.9645266745496279
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.8863335950189204
   - task:
       name: Lexical Relation Classification (ROOT09)
       type: classification
@@ -169,10 +169,10 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: None
+      value: 0.9169539329363836
     - name: F1 (macro)
       type: f1_macro
-      value: None
+      value: 0.9154665997245486
 
 ---
 # relbert/relbert-roberta-large-nce-c-semeval2012
@@ -189,11 +189,11 @@ This model achieves the following results on the relation understanding tasks:
     - Accuracy on ConceptNet Analogy: 0.43288590604026844
     - Accuracy on T-Rex Analogy: 0.6120218579234973
 - Lexical Relation Classification ([dataset](https://huggingface.co/datasets/relbert/lexical_relation_classification), [full result](https://huggingface.co/relbert/relbert-roberta-large-nce-c-semeval2012/raw/main/classification.json)):
-    - Micro F1 score on BLESS: None
-    - Micro F1 score on CogALexV: None
-    - Micro F1 score on EVALution: None
-    - Micro F1 score on K&H+N: None
-    - Micro F1 score on ROOT09: None
+    - Micro F1 score on BLESS: 0.9240620762392647
+    - Micro F1 score on CogALexV: 0.8697183098591549
+    - Micro F1 score on EVALution: 0.7145178764897074
+    - Micro F1 score on K&H+N: 0.9645266745496279
+    - Micro F1 score on ROOT09: 0.9169539329363836
 - Relation Mapping ([dataset](https://huggingface.co/datasets/relbert/relation_mapping), [full result](https://huggingface.co/relbert/relbert-roberta-large-nce-c-semeval2012/raw/main/relation_mapping.json)):
     - Accuracy on Relation Mapping: 0.7419444444444444 
 

classification.json

@@ -0,0 +1 @@
+{"lexical_relation_classification/BLESS": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.9240620762392647, "test/f1_macro": 0.9209428077000147, "test/f1_micro": 0.9240620762392647, "test/p_macro": 0.9183376095085984, "test/p_micro": 0.9240620762392647, "test/r_macro": 0.9239499071249617, "test/r_micro": 0.9240620762392647}, "lexical_relation_classification/CogALexV": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.8697183098591549, "test/f1_macro": 0.7120211843349907, "test/f1_micro": 0.8697183098591549, "test/p_macro": 0.737898070486037, "test/p_micro": 0.8697183098591549, "test/r_macro": 0.689818193406024, "test/r_micro": 0.8697183098591549}, "lexical_relation_classification/EVALution": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.7145178764897074, "test/f1_macro": 0.6950368132437731, "test/f1_micro": 0.7145178764897074, "test/p_macro": 0.7041104371877797, "test/p_micro": 0.7145178764897074, "test/r_macro": 0.6887097932903111, "test/r_micro": 0.7145178764897074}, "lexical_relation_classification/K&H+N": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.9645266745496279, "test/f1_macro": 0.8863335950189204, "test/f1_micro": 0.9645266745496279, "test/p_macro": 0.9079614678282015, "test/p_micro": 0.9645266745496279, "test/r_macro": 0.8678882336276468, "test/r_micro": 0.9645266745496279}, "lexical_relation_classification/ROOT09": {"classifier_config": {"activation": "relu", "alpha": 0.0001, "batch_size": "auto", "beta_1": 0.9, "beta_2": 0.999, "early_stopping": false, "epsilon": 1e-08, "hidden_layer_sizes": [100], "learning_rate": "constant", "learning_rate_init": 0.001, "max_fun": 15000, "max_iter": 200, "momentum": 0.9, "n_iter_no_change": 10, "nesterovs_momentum": true, "power_t": 0.5, "random_state": 0, "shuffle": true, "solver": "adam", "tol": 0.0001, "validation_fraction": 0.1, "verbose": false, "warm_start": false}, "test/accuracy": 0.9169539329363836, "test/f1_macro": 0.9154665997245486, "test/f1_micro": 0.9169539329363836, "test/p_macro": 0.9187042989342739, "test/p_micro": 0.9169539329363836, "test/r_macro": 0.9124356845305504, "test/r_micro": 0.9169539329363836}}

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "relbert_output/ckpt/nce_semeval2012/template-c/epoch_6",
+  "_name_or_path": "roberta-large",
   "architectures": [
     "RobertaModel"
   ],

tokenizer_config.json

@@ -6,7 +6,7 @@
   "errors": "replace",
   "mask_token": "<mask>",
   "model_max_length": 512,
-  "name_or_path": "relbert_output/ckpt/nce_semeval2012/template-c/epoch_6",
+  "name_or_path": "roberta-large",
   "pad_token": "<pad>",
   "sep_token": "</s>",
   "special_tokens_map_file": null,