init

config.json

@@ -0,0 +1,78 @@
+{
+  "_name_or_path": "xlm-roberta-base",
+  "architectures": [
+    "XLMRobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "B-actor",
+    "1": "I-actor",
+    "2": "O",
+    "3": "B-plot",
+    "4": "I-plot",
+    "5": "B-opinion",
+    "6": "I-opinion",
+    "7": "B-award",
+    "8": "I-award",
+    "9": "B-date",
+    "10": "B-genre",
+    "11": "B-origin",
+    "12": "I-origin",
+    "13": "B-director",
+    "14": "I-director",
+    "15": "I-genre",
+    "16": "I-date",
+    "17": "B-soundtrack",
+    "18": "I-soundtrack",
+    "19": "B-relationship",
+    "20": "I-relationship",
+    "21": "B-character name",
+    "22": "I-character name",
+    "23": "B-quote",
+    "24": "I-quote"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-actor": 0,
+    "B-award": 7,
+    "B-character name": 21,
+    "B-date": 9,
+    "B-director": 13,
+    "B-genre": 10,
+    "B-opinion": 5,
+    "B-origin": 11,
+    "B-plot": 3,
+    "B-quote": 23,
+    "B-relationship": 19,
+    "B-soundtrack": 17,
+    "I-actor": 1,
+    "I-award": 8,
+    "I-character name": 22,
+    "I-date": 16,
+    "I-director": 14,
+    "I-genre": 15,
+    "I-opinion": 6,
+    "I-origin": 12,
+    "I-plot": 4,
+    "I-quote": 24,
+    "I-relationship": 20,
+    "I-soundtrack": 18,
+    "O": 2
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "type_vocab_size": 1,
+  "vocab_size": 250002
+}

parameter.json

@@ -0,0 +1 @@
+{"dataset": ["mit_movie_trivia"], "transformers_model": "xlm-roberta-base", "random_seed": 1234, "lr": 1e-05, "total_step": 13000, "warmup_step": 700, "weight_decay": 1e-07, "batch_size": 16, "max_seq_length": 128, "fp16": false, "max_grad_norm": 1.0, "lower_case": true}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:82c48dcf471eb7607e112d9d40445c05cbea3c76ef0051d30b4fa50ac00ad8f9
+size 1109973825

sentencepiece.bpe.model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
+size 5069051

special_tokens_map.json

@@ -0,0 +1 @@
+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>"}

test_bc5cdr_span_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}, "test": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_bionlp2004_span_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_conll2003_span_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}, "test": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_fin_span_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_mit_movie_trivia_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 69.98644986449864, "recall": 72.66971508969398, "precision": 67.49428291408036, "summary": "                precision    recall  f1-score   support\n\n         actor       0.92      0.96      0.94      1274\n         award       0.39      0.44      0.41        66\ncharacter name       0.64      0.71      0.67       283\n          date       0.95      0.97      0.96       661\n      director       0.85      0.92      0.88       425\n         genre       0.71      0.75      0.73       789\n       opinion       0.36      0.45      0.40       195\n        origin       0.30      0.35      0.33       190\n          plot       0.45      0.49      0.47      1577\n         quote       0.62      0.72      0.67        47\n  relationship       0.51      0.54      0.52       171\n    soundtrack       0.11      0.25      0.15         8\n\n     micro avg       0.67      0.73      0.70      5686\n     macro avg       0.57      0.63      0.59      5686\n  weighted avg       0.68      0.73      0.70      5686\n"}}

test_mit_movie_trivia_span_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 73.1065139340058, "recall": 75.20225114315863, "precision": 71.12441783100466, "summary": "              precision    recall  f1-score   support\n\n      entity       0.71      0.75      0.73      5686\n\n   micro avg       0.71      0.75      0.73      5686\n   macro avg       0.71      0.75      0.73      5686\nweighted avg       0.71      0.75      0.73      5686\n"}}

test_mit_restaurant_span_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_ontonotes5_span_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 15.867944621938236, "recall": 9.887193098871931, "precision": 40.16172506738545, "summary": "              precision    recall  f1-score   support\n\n      entity       0.40      0.10      0.16      1507\n\n   micro avg       0.40      0.10      0.16      1507\n   macro avg       0.40      0.10      0.16      1507\nweighted avg       0.40      0.10      0.16      1507\n"}, "test": {"f1": 14.532520325203253, "recall": 8.931917551530294, "precision": 38.96457765667575, "summary": "              precision    recall  f1-score   support\n\n      entity       0.39      0.09      0.15      1601\n\n   micro avg       0.39      0.09      0.15      1601\n   macro avg       0.39      0.09      0.15      1601\nweighted avg       0.39      0.09      0.15      1601\n"}}

test_panx_dataset-en_span_lower.json

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+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}, "test": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_wnut2017_span_lower.json

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+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}, "test": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

tokenizer_config.json

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+{"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "model_max_length": 512, "name_or_path": "xlm-roberta-base"}