haryoaw commited on
Commit
4ce2e85
1 Parent(s): d91612b

Initial Commit

Browse files
Files changed (5) hide show
  1. README.md +61 -31
  2. config.json +13 -20
  3. eval_result_ner.json +1 -1
  4. model.safetensors +2 -2
  5. training_args.bin +1 -1
README.md CHANGED
@@ -1,14 +1,14 @@
1
  ---
2
- base_model: haryoaw/scenario-TCR-NER_data-univner_half
3
  library_name: transformers
4
  license: mit
 
 
 
5
  metrics:
6
  - precision
7
  - recall
8
  - f1
9
  - accuracy
10
- tags:
11
- - generated_from_trainer
12
  model-index:
13
  - name: scenario-kd-scr-ner-full_data-univner_full44
14
  results: []
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
21
 
22
  This model is a fine-tuned version of [haryoaw/scenario-TCR-NER_data-univner_half](https://huggingface.co/haryoaw/scenario-TCR-NER_data-univner_half) on the None dataset.
23
  It achieves the following results on the evaluation set:
24
- - Loss: nan
25
- - Precision: 0.0
26
- - Recall: 0.0
27
- - F1: 0.0
28
- - Accuracy: 0.9241
29
 
30
  ## Model description
31
 
@@ -54,29 +54,59 @@ The following hyperparameters were used during training:
54
 
55
  ### Training results
56
 
57
- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
58
- |:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:---:|:--------:|
59
- | 4.7751 | 0.5828 | 500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
60
- | 0.0 | 1.1655 | 1000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
61
- | 0.0 | 1.7483 | 1500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
62
- | 0.0 | 2.3310 | 2000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
63
- | 0.0 | 2.9138 | 2500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
64
- | 0.0 | 3.4965 | 3000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
65
- | 0.0 | 4.0793 | 3500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
66
- | 0.0 | 4.6620 | 4000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
67
- | 0.0 | 5.2448 | 4500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
68
- | 0.0 | 5.8275 | 5000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
69
- | 0.0 | 6.4103 | 5500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
70
- | 0.0 | 6.9930 | 6000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
71
- | 0.0 | 7.5758 | 6500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
72
- | 0.0 | 8.1585 | 7000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
73
- | 0.0 | 8.7413 | 7500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
74
- | 0.0 | 9.3240 | 8000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
75
- | 0.0 | 9.9068 | 8500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
76
- | 0.0 | 10.4895 | 9000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
77
- | 0.0 | 11.0723 | 9500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
78
- | 0.0 | 11.6550 | 10000 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
79
- | 0.0 | 12.2378 | 10500 | nan | 0.0 | 0.0 | 0.0 | 0.9241 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
80
 
81
 
82
  ### Framework versions
 
1
  ---
 
2
  library_name: transformers
3
  license: mit
4
+ base_model: haryoaw/scenario-TCR-NER_data-univner_half
5
+ tags:
6
+ - generated_from_trainer
7
  metrics:
8
  - precision
9
  - recall
10
  - f1
11
  - accuracy
 
 
12
  model-index:
13
  - name: scenario-kd-scr-ner-full_data-univner_full44
14
  results: []
 
21
 
22
  This model is a fine-tuned version of [haryoaw/scenario-TCR-NER_data-univner_half](https://huggingface.co/haryoaw/scenario-TCR-NER_data-univner_half) on the None dataset.
23
  It achieves the following results on the evaluation set:
24
+ - Loss: 1.6199
25
+ - Precision: 0.4352
26
+ - Recall: 0.3701
27
+ - F1: 0.4000
28
+ - Accuracy: 0.9387
29
 
30
  ## Model description
31
 
 
54
 
55
  ### Training results
56
 
57
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
58
+ |:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
59
+ | 2.9268 | 0.5828 | 500 | 2.5728 | 0.4130 | 0.0082 | 0.0161 | 0.9245 |
60
+ | 2.2111 | 1.1655 | 1000 | 2.6038 | 0.2535 | 0.0757 | 0.1166 | 0.9230 |
61
+ | 1.9667 | 1.7483 | 1500 | 2.4899 | 0.2074 | 0.1753 | 0.1900 | 0.9168 |
62
+ | 1.7467 | 2.3310 | 2000 | 2.1434 | 0.3184 | 0.1717 | 0.2231 | 0.9291 |
63
+ | 1.6429 | 2.9138 | 2500 | 2.1913 | 0.2798 | 0.1997 | 0.2330 | 0.9274 |
64
+ | 1.4992 | 3.4965 | 3000 | 2.0144 | 0.2988 | 0.2192 | 0.2529 | 0.9291 |
65
+ | 1.3977 | 4.0793 | 3500 | 2.0470 | 0.3052 | 0.2575 | 0.2793 | 0.9284 |
66
+ | 1.2778 | 4.6620 | 4000 | 2.1220 | 0.3168 | 0.2727 | 0.2931 | 0.9248 |
67
+ | 1.2224 | 5.2448 | 4500 | 1.9196 | 0.3273 | 0.2679 | 0.2946 | 0.9303 |
68
+ | 1.1262 | 5.8275 | 5000 | 1.9602 | 0.3120 | 0.3111 | 0.3115 | 0.9280 |
69
+ | 1.0371 | 6.4103 | 5500 | 2.0035 | 0.3100 | 0.3189 | 0.3144 | 0.9238 |
70
+ | 1.0053 | 6.9930 | 6000 | 1.8674 | 0.3395 | 0.2821 | 0.3081 | 0.9303 |
71
+ | 0.9232 | 7.5758 | 6500 | 1.8771 | 0.3290 | 0.3262 | 0.3276 | 0.9303 |
72
+ | 0.872 | 8.1585 | 7000 | 1.8623 | 0.3228 | 0.3269 | 0.3249 | 0.9286 |
73
+ | 0.8387 | 8.7413 | 7500 | 1.8017 | 0.3676 | 0.3295 | 0.3475 | 0.9341 |
74
+ | 0.7799 | 9.3240 | 8000 | 1.9406 | 0.2966 | 0.3473 | 0.3200 | 0.9220 |
75
+ | 0.7627 | 9.9068 | 8500 | 1.8042 | 0.3618 | 0.3474 | 0.3545 | 0.9336 |
76
+ | 0.7129 | 10.4895 | 9000 | 1.7746 | 0.3609 | 0.3440 | 0.3522 | 0.9355 |
77
+ | 0.6964 | 11.0723 | 9500 | 1.7343 | 0.4023 | 0.3438 | 0.3708 | 0.9379 |
78
+ | 0.6547 | 11.6550 | 10000 | 1.7256 | 0.3996 | 0.3616 | 0.3796 | 0.9366 |
79
+ | 0.6363 | 12.2378 | 10500 | 1.7899 | 0.3701 | 0.3735 | 0.3718 | 0.9319 |
80
+ | 0.6183 | 12.8205 | 11000 | 1.8503 | 0.3564 | 0.3575 | 0.3570 | 0.9280 |
81
+ | 0.5881 | 13.4033 | 11500 | 1.7546 | 0.3679 | 0.3708 | 0.3693 | 0.9325 |
82
+ | 0.5822 | 13.9860 | 12000 | 1.6888 | 0.4090 | 0.3331 | 0.3672 | 0.9371 |
83
+ | 0.5475 | 14.5688 | 12500 | 1.6986 | 0.4197 | 0.3507 | 0.3821 | 0.9371 |
84
+ | 0.5396 | 15.1515 | 13000 | 1.7398 | 0.3979 | 0.3698 | 0.3833 | 0.9344 |
85
+ | 0.5248 | 15.7343 | 13500 | 1.7333 | 0.3914 | 0.3620 | 0.3761 | 0.9340 |
86
+ | 0.5096 | 16.3170 | 14000 | 1.6605 | 0.4354 | 0.3561 | 0.3918 | 0.9388 |
87
+ | 0.5037 | 16.8998 | 14500 | 1.7022 | 0.3882 | 0.3771 | 0.3826 | 0.9355 |
88
+ | 0.4839 | 17.4825 | 15000 | 1.6857 | 0.4071 | 0.3587 | 0.3814 | 0.9365 |
89
+ | 0.4769 | 18.0653 | 15500 | 1.6599 | 0.4432 | 0.3516 | 0.3921 | 0.9389 |
90
+ | 0.4607 | 18.6480 | 16000 | 1.6403 | 0.4445 | 0.3650 | 0.4009 | 0.9396 |
91
+ | 0.4567 | 19.2308 | 16500 | 1.6463 | 0.4321 | 0.3546 | 0.3895 | 0.9388 |
92
+ | 0.4449 | 19.8135 | 17000 | 1.6771 | 0.4148 | 0.3836 | 0.3986 | 0.9366 |
93
+ | 0.4363 | 20.3963 | 17500 | 1.7157 | 0.3993 | 0.3735 | 0.3860 | 0.9341 |
94
+ | 0.437 | 20.9790 | 18000 | 1.6571 | 0.4148 | 0.3738 | 0.3932 | 0.9372 |
95
+ | 0.4221 | 21.5618 | 18500 | 1.6544 | 0.4196 | 0.3582 | 0.3865 | 0.9372 |
96
+ | 0.4168 | 22.1445 | 19000 | 1.6168 | 0.4472 | 0.3428 | 0.3881 | 0.9399 |
97
+ | 0.409 | 22.7273 | 19500 | 1.6285 | 0.4335 | 0.3572 | 0.3917 | 0.9388 |
98
+ | 0.4081 | 23.3100 | 20000 | 1.6653 | 0.4058 | 0.3758 | 0.3903 | 0.9353 |
99
+ | 0.4009 | 23.8928 | 20500 | 1.6389 | 0.4263 | 0.3662 | 0.3940 | 0.9380 |
100
+ | 0.3886 | 24.4755 | 21000 | 1.6027 | 0.4632 | 0.3657 | 0.4087 | 0.9407 |
101
+ | 0.3947 | 25.0583 | 21500 | 1.6297 | 0.4377 | 0.3632 | 0.3969 | 0.9387 |
102
+ | 0.3839 | 25.6410 | 22000 | 1.6285 | 0.4317 | 0.3670 | 0.3968 | 0.9384 |
103
+ | 0.382 | 26.2238 | 22500 | 1.6517 | 0.4226 | 0.3740 | 0.3968 | 0.9372 |
104
+ | 0.3797 | 26.8065 | 23000 | 1.6248 | 0.4441 | 0.3711 | 0.4043 | 0.9389 |
105
+ | 0.3748 | 27.3893 | 23500 | 1.6254 | 0.4379 | 0.3754 | 0.4043 | 0.9388 |
106
+ | 0.3736 | 27.9720 | 24000 | 1.6162 | 0.4515 | 0.3659 | 0.4042 | 0.9392 |
107
+ | 0.3714 | 28.5548 | 24500 | 1.6312 | 0.4289 | 0.3748 | 0.4001 | 0.9380 |
108
+ | 0.3719 | 29.1375 | 25000 | 1.6199 | 0.4390 | 0.3720 | 0.4027 | 0.9384 |
109
+ | 0.3684 | 29.7203 | 25500 | 1.6199 | 0.4352 | 0.3701 | 0.4000 | 0.9387 |
110
 
111
 
112
  ### Framework versions
config.json CHANGED
@@ -1,9 +1,12 @@
1
  {
2
  "_name_or_path": "haryoaw/scenario-TCR-NER_data-univner_half",
3
  "architectures": [
4
- "DebertaForTokenClassificationKD"
5
  ],
6
  "attention_probs_dropout_prob": 0.1,
 
 
 
7
  "hidden_act": "gelu",
8
  "hidden_dropout_prob": 0.1,
9
  "hidden_size": 768,
@@ -27,27 +30,17 @@
27
  "LABEL_5": 5,
28
  "LABEL_6": 6
29
  },
30
- "layer_norm_eps": 1e-07,
31
- "max_position_embeddings": 512,
32
- "max_relative_positions": -1,
33
- "model_type": "deberta-v2",
34
- "norm_rel_ebd": "layer_norm",
35
  "num_attention_heads": 12,
36
  "num_hidden_layers": 6,
37
- "pad_token_id": 0,
38
- "pooler_dropout": 0,
39
- "pooler_hidden_act": "gelu",
40
- "pooler_hidden_size": 768,
41
- "pos_att_type": [
42
- "p2c",
43
- "c2p"
44
- ],
45
- "position_biased_input": false,
46
- "position_buckets": 256,
47
- "relative_attention": true,
48
- "share_att_key": true,
49
  "torch_dtype": "float32",
50
  "transformers_version": "4.44.2",
51
- "type_vocab_size": 0,
52
- "vocab_size": 251000
 
53
  }
 
1
  {
2
  "_name_or_path": "haryoaw/scenario-TCR-NER_data-univner_half",
3
  "architectures": [
4
+ "XLMRobertaForTokenClassificationKD"
5
  ],
6
  "attention_probs_dropout_prob": 0.1,
7
+ "bos_token_id": 0,
8
+ "classifier_dropout": null,
9
+ "eos_token_id": 2,
10
  "hidden_act": "gelu",
11
  "hidden_dropout_prob": 0.1,
12
  "hidden_size": 768,
 
30
  "LABEL_5": 5,
31
  "LABEL_6": 6
32
  },
33
+ "layer_norm_eps": 1e-05,
34
+ "max_position_embeddings": 514,
35
+ "model_type": "xlm-roberta",
 
 
36
  "num_attention_heads": 12,
37
  "num_hidden_layers": 6,
38
+ "output_past": true,
39
+ "pad_token_id": 1,
40
+ "position_embedding_type": "absolute",
 
 
 
 
 
 
 
 
 
41
  "torch_dtype": "float32",
42
  "transformers_version": "4.44.2",
43
+ "type_vocab_size": 1,
44
+ "use_cache": true,
45
+ "vocab_size": 250002
46
  }
eval_result_ner.json CHANGED
@@ -1 +1 @@
1
- {"ceb_gja": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9606177606177606}, "en_pud": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9260955799017756}, "de_pud": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9299142093666495}, "pt_pud": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9310035459477934}, "ru_pud": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9235856367863601}, "sv_pud": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9247221639756762}, "tl_trg": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9673024523160763}, "tl_ugnayan": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9525979945305378}, "zh_gsd": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.8823676323676324}, "zh_gsdsimp": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.8828671328671329}, "hr_set": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9144270403957131}, "da_ddt": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9357477801057568}, "en_ewt": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9330995736542216}, "pt_bosque": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9222576438197363}, "sr_set": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.8929165572191577}, "sk_snk": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.8910961055276382}, "sv_talbanken": {"precision": 0.0, "recall": 0.0, "f1": 0.0, "accuracy": 0.9881729400795014}}
 
1
+ {"ceb_gja": {"precision": 0.4, "recall": 0.24489795918367346, "f1": 0.30379746835443044, "accuracy": 0.9552123552123553}, "en_pud": {"precision": 0.4603825136612022, "recall": 0.31348837209302327, "f1": 0.3729939125622579, "accuracy": 0.9435209671326029}, "de_pud": {"precision": 0.1388888888888889, "recall": 0.12993262752646775, "f1": 0.1342615614122327, "accuracy": 0.892363227227978}, "pt_pud": {"precision": 0.268348623853211, "recall": 0.10646041856232939, "f1": 0.152442996742671, "accuracy": 0.928739266031529}, "ru_pud": {"precision": 0.015625, "recall": 0.015444015444015444, "f1": 0.015533980582524271, "accuracy": 0.8305347455437871}, "sv_pud": {"precision": 0.18719211822660098, "recall": 0.11078717201166181, "f1": 0.1391941391941392, "accuracy": 0.9084189557559237}, "tl_trg": {"precision": 0.5263157894736842, "recall": 0.43478260869565216, "f1": 0.47619047619047616, "accuracy": 0.9686648501362398}, "tl_ugnayan": {"precision": 0.03571428571428571, "recall": 0.030303030303030304, "f1": 0.03278688524590164, "accuracy": 0.9334548769371012}, "zh_gsd": {"precision": 0.5314787701317716, "recall": 0.47327249022164275, "f1": 0.5006896551724138, "accuracy": 0.9335664335664335}, "zh_gsdsimp": {"precision": 0.48214285714285715, "recall": 0.42463958060288337, "f1": 0.4515679442508711, "accuracy": 0.9289044289044289}, "hr_set": {"precision": 0.6854014598540146, "recall": 0.66928011404134, "f1": 0.6772448611611973, "accuracy": 0.9651690024732069}, "da_ddt": {"precision": 0.25, "recall": 0.12304250559284116, "f1": 0.16491754122938532, "accuracy": 0.934949615883468}, "en_ewt": {"precision": 0.5731272294887039, "recall": 0.4430147058823529, "f1": 0.4997407983411093, "accuracy": 0.9567677411642825}, "pt_bosque": {"precision": 0.20082815734989648, "recall": 0.07983539094650206, "f1": 0.11425206124852769, "accuracy": 0.9212795247065643}, "sr_set": {"precision": 0.6670902160101652, "recall": 0.6198347107438017, "f1": 0.642594859241126, "accuracy": 0.9485158917783031}, "sk_snk": {"precision": 0.19081272084805653, "recall": 0.1180327868852459, "f1": 0.14584740040513167, "accuracy": 0.8800251256281407}, "sv_talbanken": {"precision": 0.055401662049861494, "recall": 0.10204081632653061, "f1": 0.0718132854578097, "accuracy": 0.9638808460519213}}
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:a17e1b58722cbfa169073c590fa2d17fb6cba0d515b0020d5211ca6310aad01a
3
- size 972678148
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bd465ad3d3ec511cbd82db1bbc532be7c983c7c94d7e2635d542dec208f75228
3
+ size 939737140
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:6b6ca5c5c8a1b9eeca8cd69173da207af99504dad2548035a5b3ad2094c73ac0
3
  size 5304
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:868ddb0c64e7be3d1d948649bc919954f9c67150bfdd30ad601ec98990942154
3
  size 5304