asahi417 commited on
Commit
0514a6e
1 Parent(s): 7824e5b
config.json ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "xlm-roberta-base",
3
+ "architectures": [
4
+ "XLMRobertaForTokenClassification"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "bos_token_id": 0,
8
+ "eos_token_id": 2,
9
+ "gradient_checkpointing": false,
10
+ "hidden_act": "gelu",
11
+ "hidden_dropout_prob": 0.1,
12
+ "hidden_size": 768,
13
+ "id2label": {
14
+ "0": "O",
15
+ "1": "B-location",
16
+ "2": "I-location",
17
+ "3": "B-group",
18
+ "4": "B-corporation",
19
+ "5": "B-person",
20
+ "6": "B-work of art",
21
+ "7": "B-product",
22
+ "8": "I-person",
23
+ "9": "I-work of art",
24
+ "10": "I-corporation",
25
+ "11": "I-group",
26
+ "12": "I-product"
27
+ },
28
+ "initializer_range": 0.02,
29
+ "intermediate_size": 3072,
30
+ "label2id": {
31
+ "B-corporation": 4,
32
+ "B-group": 3,
33
+ "B-location": 1,
34
+ "B-person": 5,
35
+ "B-product": 7,
36
+ "B-work of art": 6,
37
+ "I-corporation": 10,
38
+ "I-group": 11,
39
+ "I-location": 2,
40
+ "I-person": 8,
41
+ "I-product": 12,
42
+ "I-work of art": 9,
43
+ "O": 0
44
+ },
45
+ "layer_norm_eps": 1e-05,
46
+ "max_position_embeddings": 514,
47
+ "model_type": "xlm-roberta",
48
+ "num_attention_heads": 12,
49
+ "num_hidden_layers": 12,
50
+ "output_past": true,
51
+ "pad_token_id": 1,
52
+ "type_vocab_size": 1,
53
+ "vocab_size": 250002
54
+ }
parameter.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"dataset": ["wnut2017"], "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": false}
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:456f1656e7e629890ce5838dd4f13092a758cc77086283c4c0933fe1420979cf
3
+ size 1109937680
sentencepiece.bpe.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
3
+ size 5069051
special_tokens_map.json ADDED
@@ -0,0 +1 @@
 
 
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.json ADDED
@@ -0,0 +1 @@
 
 
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.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}
test_conll2003_span.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"valid": {"f1": 83.91780821917808, "recall": 83.64281813216822, "precision": 84.19461242440902, "summary": " precision recall f1-score support\n\n entity 0.84 0.84 0.84 3662\n\n micro avg 0.84 0.84 0.84 3662\n macro avg 0.84 0.84 0.84 3662\nweighted avg 0.84 0.84 0.84 3662\n"}, "test": {"f1": 81.24999999999999, "recall": 81.89602446483181, "precision": 80.61408789885611, "summary": " precision recall f1-score support\n\n entity 0.81 0.82 0.81 3270\n\n micro avg 0.81 0.82 0.81 3270\n macro avg 0.81 0.82 0.81 3270\nweighted avg 0.81 0.82 0.81 3270\n"}}
test_fin_span.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"valid": {"f1": 20.51282051282051, "recall": 13.861386138613863, "precision": 39.436619718309856, "summary": " precision recall f1-score support\n\n entity 0.39 0.14 0.21 202\n\n micro avg 0.39 0.14 0.21 202\n macro avg 0.39 0.14 0.21 202\nweighted avg 0.39 0.14 0.21 202\n"}}
test_ontonotes5_span.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"valid": {"f1": 39.880188275566965, "recall": 56.84659957304056, "precision": 30.713461855330365, "summary": " precision recall f1-score support\n\n entity 0.31 0.57 0.40 3279\n\n micro avg 0.31 0.57 0.40 3279\n macro avg 0.31 0.57 0.40 3279\nweighted avg 0.31 0.57 0.40 3279\n"}, "test": {"f1": 41.320320210549404, "recall": 57.969230769230776, "precision": 32.10086897256773, "summary": " precision recall f1-score support\n\n entity 0.32 0.58 0.41 3250\n\n micro avg 0.32 0.58 0.41 3250\n macro avg 0.32 0.58 0.41 3250\nweighted avg 0.32 0.58 0.41 3250\n"}}
test_panx_dataset-en_span.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"valid": {"f1": 56.800000000000004, "recall": 63.943632125450314, "precision": 51.092109718929905, "summary": " precision recall f1-score support\n\n entity 0.51 0.64 0.57 9438\n\n micro avg 0.51 0.64 0.57 9438\n macro avg 0.51 0.64 0.57 9438\nweighted avg 0.51 0.64 0.57 9438\n"}, "test": {"f1": 56.25512616394075, "recall": 63.71584699453552, "precision": 50.35846937894101, "summary": " precision recall f1-score support\n\n entity 0.50 0.64 0.56 9150\n\n micro avg 0.50 0.64 0.56 9150\n macro avg 0.50 0.64 0.56 9150\nweighted avg 0.50 0.64 0.56 9150\n"}}
test_wnut2017.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"valid": {"f1": 62.81879194630873, "recall": 55.980861244019145, "precision": 71.55963302752293, "summary": " precision recall f1-score support\n\n corporation 0.43 0.38 0.41 34\n group 0.25 0.26 0.25 39\n location 0.66 0.61 0.63 74\n person 0.86 0.71 0.77 470\n product 0.59 0.36 0.45 114\n work of art 0.46 0.26 0.33 105\n\n micro avg 0.72 0.56 0.63 836\n macro avg 0.54 0.43 0.47 836\nweighted avg 0.71 0.56 0.62 836\n"}, "test": {"f1": 52.844638949671776, "recall": 44.84679665738162, "precision": 64.31424766977364, "summary": " precision recall f1-score support\n\n corporation 0.33 0.32 0.33 66\n group 0.48 0.28 0.35 165\n location 0.67 0.58 0.62 150\n person 0.81 0.62 0.70 428\n product 0.33 0.17 0.23 127\n work of art 0.61 0.30 0.41 141\n\n micro avg 0.64 0.45 0.53 1077\n macro avg 0.54 0.38 0.44 1077\nweighted avg 0.63 0.45 0.52 1077\n"}}
test_wnut2017_span.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"valid": {"f1": 73.03295225285811, "recall": 64.95215311004785, "precision": 83.41013824884793, "summary": " precision recall f1-score support\n\n entity 0.83 0.65 0.73 836\n\n micro avg 0.83 0.65 0.73 836\n macro avg 0.83 0.65 0.73 836\nweighted avg 0.83 0.65 0.73 836\n"}, "test": {"f1": 63.00164925783397, "recall": 53.2033426183844, "precision": 77.22371967654986, "summary": " precision recall f1-score support\n\n entity 0.77 0.53 0.63 1077\n\n micro avg 0.77 0.53 0.63 1077\n macro avg 0.77 0.53 0.63 1077\nweighted avg 0.77 0.53 0.63 1077\n"}}
tokenizer_config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"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"}