model update

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "cner_output/model/baseline_2021/bert_large_continuous/best_model",
+  "_name_or_path": "cner_output/model/baseline_2021/bert_large_continuous/model_rgztrs/epoch_10",
   "architectures": [
     "BertForTokenClassification"
   ],

eval/metric.json

@@ -0,0 +1 @@
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"recall": 0.6450617283950617}}}, "2020.test": {"micro/f1": 0.627504803733187, "micro/f1_ci": {"90": [0.6078024011269899, 0.6467617272138512], "95": [0.6025030891438657, 0.6507360960005407]}, "micro/recall": 0.593149974052932, "micro/precision": 0.666083916083916, "macro/f1": 0.5827528080574257, "macro/f1_ci": {"90": [0.5599042876690897, 0.6019886567212679], "95": [0.5555869022704765, 0.606586096332577]}, "macro/recall": 0.5511628178433657, "macro/precision": 0.6224454542533556, "per_entity_metric": {"corporation": {"f1": 0.5684754521963824, "f1_ci": {"90": [0.5056148564294631, 0.6216629895201323], "95": [0.49395143599608515, 0.6334164588528679]}, "precision": 0.5612244897959183, "recall": 0.5759162303664922}, "creative_work": {"f1": 0.44712990936555896, "f1_ci": {"90": [0.38530791943477805, 0.5048748083801737], "95": [0.37419245117401795, 0.5147080577793248]}, "precision": 0.4868421052631579, "recall": 0.4134078212290503}, "event": {"f1": 0.42168674698795183, "f1_ci": {"90": 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(span detection)": {"micro/f1": 0.7699616507355046, "micro/f1_ci": {}, "micro/recall": 0.7778420261362322, "micro/precision": 0.7622393472348141, "macro/f1": 0.7699616507355046, "macro/f1_ci": {}, "macro/recall": 0.7778420261362322, "macro/precision": 0.7622393472348141}, "2020.test (span detection)": {"micro/f1": 0.7309170785282812, "micro/f1_ci": {}, "micro/recall": 0.6907109496626881, "micro/precision": 0.7760932944606413, "macro/f1": 0.7309170785282812, "macro/f1_ci": {}, "macro/recall": 0.6907109496626881, "macro/precision": 0.7760932944606413}}

pytorch_model.bin

@@ -1,3 +1,3 @@
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-size 1330337393
+oid sha256:57f852896a5f9430d01e63656a173e5c7c6b38034c82ee80d98c07781ac705a3
+size 1330342897

tokenizer_config.json

@@ -1 +1 @@
-{"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "name_or_path": "cner_output/model/baseline_2021/bert_large_continuous/best_model", "special_tokens_map_file": "/home/c.c2042013/.cache/huggingface/transformers/dedfc9f0e4ac921a476db22ccb98cf583956e8496609dd41a02a6c13a4221c7a.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "tokenizer_class": "BertTokenizer"}
+{"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "name_or_path": "cner_output/model/baseline_2021/bert_large_continuous/model_rgztrs/epoch_10", "special_tokens_map_file": "/home/c.c2042013/.cache/huggingface/transformers/dedfc9f0e4ac921a476db22ccb98cf583956e8496609dd41a02a6c13a4221c7a.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "tokenizer_class": "BertTokenizer"}

trainer_config.json

@@ -0,0 +1 @@
+{"data_split": "2021.train", "model": "tner/bert-large-tweetner-2020", "crf": true, "max_length": 128, "epoch": 30, "batch_size": 32, "lr": 1e-06, "random_seed": 0, "gradient_accumulation_steps": 1, "weight_decay": 1e-07, "lr_warmup_step_ratio": 0.3, "max_grad_norm": 1}