Initial Commit
Browse files- README.md +59 -59
- config.json +1 -1
- eval_result_ner.json +1 -1
- model.safetensors +2 -2
- 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-non-kd-po-ner-full-xlmr_data-univner_half44
|
| 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: 0.
|
| 25 |
-
- Precision: 0.
|
| 26 |
-
- Recall: 0.
|
| 27 |
-
- F1: 0.
|
| 28 |
-
- Accuracy: 0.
|
| 29 |
|
| 30 |
## Model description
|
| 31 |
|
|
@@ -56,57 +56,57 @@ The following hyperparameters were used during training:
|
|
| 56 |
|
| 57 |
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 58 |
|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 59 |
-
| 0.
|
| 60 |
-
| 0.
|
| 61 |
-
| 0.
|
| 62 |
-
| 0.
|
| 63 |
-
| 0.
|
| 64 |
-
| 0.
|
| 65 |
-
| 0.
|
| 66 |
-
| 0.
|
| 67 |
-
| 0.
|
| 68 |
-
| 0.
|
| 69 |
-
| 0.
|
| 70 |
-
| 0.
|
| 71 |
-
| 0.
|
| 72 |
-
| 0.
|
| 73 |
-
| 0.
|
| 74 |
-
| 0.
|
| 75 |
-
| 0.
|
| 76 |
-
| 0.
|
| 77 |
-
| 0.
|
| 78 |
-
| 0.0024 | 11.6550 | 10000 | 0.
|
| 79 |
-
| 0.
|
| 80 |
-
| 0.
|
| 81 |
-
| 0.
|
| 82 |
-
| 0.
|
| 83 |
-
| 0.
|
| 84 |
-
| 0.
|
| 85 |
-
| 0.
|
| 86 |
-
| 0.
|
| 87 |
-
| 0.
|
| 88 |
-
| 0.
|
| 89 |
-
| 0.
|
| 90 |
-
| 0.
|
| 91 |
-
| 0.
|
| 92 |
-
| 0.
|
| 93 |
-
| 0.
|
| 94 |
-
| 0.
|
| 95 |
-
| 0.
|
| 96 |
-
| 0.
|
| 97 |
-
| 0.
|
| 98 |
-
| 0.
|
| 99 |
-
| 0.0005 | 23.8928 | 20500 | 0.
|
| 100 |
-
| 0.
|
| 101 |
-
| 0.
|
| 102 |
-
| 0.
|
| 103 |
-
| 0.0004 | 26.2238 | 22500 | 0.
|
| 104 |
-
| 0.
|
| 105 |
-
| 0.
|
| 106 |
-
| 0.
|
| 107 |
-
| 0.
|
| 108 |
-
| 0.0003 | 29.1375 | 25000 | 0.
|
| 109 |
-
| 0.0002 | 29.7203 | 25500 | 0.
|
| 110 |
|
| 111 |
|
| 112 |
### 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-non-kd-po-ner-full-xlmr_data-univner_half44
|
| 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: 0.1624
|
| 25 |
+
- Precision: 0.8067
|
| 26 |
+
- Recall: 0.8152
|
| 27 |
+
- F1: 0.8109
|
| 28 |
+
- Accuracy: 0.9801
|
| 29 |
|
| 30 |
## Model description
|
| 31 |
|
|
|
|
| 56 |
|
| 57 |
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 58 |
|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 59 |
+
| 0.075 | 0.5828 | 500 | 0.0769 | 0.7627 | 0.7648 | 0.7638 | 0.9772 |
|
| 60 |
+
| 0.0416 | 1.1655 | 1000 | 0.0813 | 0.7656 | 0.8016 | 0.7832 | 0.9786 |
|
| 61 |
+
| 0.0287 | 1.7483 | 1500 | 0.0833 | 0.7729 | 0.7989 | 0.7857 | 0.9785 |
|
| 62 |
+
| 0.022 | 2.3310 | 2000 | 0.1011 | 0.7465 | 0.7987 | 0.7717 | 0.9767 |
|
| 63 |
+
| 0.0171 | 2.9138 | 2500 | 0.1033 | 0.7570 | 0.8166 | 0.7857 | 0.9774 |
|
| 64 |
+
| 0.0133 | 3.4965 | 3000 | 0.0985 | 0.7734 | 0.8160 | 0.7942 | 0.9786 |
|
| 65 |
+
| 0.0121 | 4.0793 | 3500 | 0.1039 | 0.7721 | 0.8120 | 0.7916 | 0.9787 |
|
| 66 |
+
| 0.0093 | 4.6620 | 4000 | 0.1150 | 0.7766 | 0.8031 | 0.7896 | 0.9781 |
|
| 67 |
+
| 0.0083 | 5.2448 | 4500 | 0.1197 | 0.7771 | 0.8194 | 0.7977 | 0.9788 |
|
| 68 |
+
| 0.0077 | 5.8275 | 5000 | 0.1180 | 0.7721 | 0.8094 | 0.7903 | 0.9784 |
|
| 69 |
+
| 0.0073 | 6.4103 | 5500 | 0.1169 | 0.7924 | 0.8061 | 0.7992 | 0.9793 |
|
| 70 |
+
| 0.0065 | 6.9930 | 6000 | 0.1201 | 0.8011 | 0.8018 | 0.8014 | 0.9791 |
|
| 71 |
+
| 0.0055 | 7.5758 | 6500 | 0.1152 | 0.7950 | 0.7958 | 0.7954 | 0.9792 |
|
| 72 |
+
| 0.0045 | 8.1585 | 7000 | 0.1259 | 0.7825 | 0.8133 | 0.7976 | 0.9790 |
|
| 73 |
+
| 0.0039 | 8.7413 | 7500 | 0.1300 | 0.7878 | 0.8101 | 0.7988 | 0.9793 |
|
| 74 |
+
| 0.0043 | 9.3240 | 8000 | 0.1279 | 0.8026 | 0.7960 | 0.7993 | 0.9792 |
|
| 75 |
+
| 0.0041 | 9.9068 | 8500 | 0.1249 | 0.8033 | 0.7997 | 0.8015 | 0.9790 |
|
| 76 |
+
| 0.0033 | 10.4895 | 9000 | 0.1315 | 0.7890 | 0.8110 | 0.7999 | 0.9793 |
|
| 77 |
+
| 0.0034 | 11.0723 | 9500 | 0.1268 | 0.7914 | 0.8005 | 0.7959 | 0.9789 |
|
| 78 |
+
| 0.0024 | 11.6550 | 10000 | 0.1354 | 0.7943 | 0.8088 | 0.8015 | 0.9798 |
|
| 79 |
+
| 0.0023 | 12.2378 | 10500 | 0.1397 | 0.8003 | 0.8130 | 0.8066 | 0.9798 |
|
| 80 |
+
| 0.0024 | 12.8205 | 11000 | 0.1428 | 0.7779 | 0.8175 | 0.7972 | 0.9788 |
|
| 81 |
+
| 0.0023 | 13.4033 | 11500 | 0.1389 | 0.7896 | 0.8070 | 0.7982 | 0.9792 |
|
| 82 |
+
| 0.0022 | 13.9860 | 12000 | 0.1429 | 0.8 | 0.8051 | 0.8025 | 0.9794 |
|
| 83 |
+
| 0.0017 | 14.5688 | 12500 | 0.1458 | 0.7922 | 0.8113 | 0.8016 | 0.9791 |
|
| 84 |
+
| 0.002 | 15.1515 | 13000 | 0.1430 | 0.7955 | 0.8121 | 0.8037 | 0.9794 |
|
| 85 |
+
| 0.0016 | 15.7343 | 13500 | 0.1487 | 0.7795 | 0.8185 | 0.7985 | 0.9789 |
|
| 86 |
+
| 0.0019 | 16.3170 | 14000 | 0.1401 | 0.7994 | 0.8044 | 0.8019 | 0.9796 |
|
| 87 |
+
| 0.0016 | 16.8998 | 14500 | 0.1468 | 0.7964 | 0.8133 | 0.8048 | 0.9797 |
|
| 88 |
+
| 0.0016 | 17.4825 | 15000 | 0.1440 | 0.7955 | 0.8100 | 0.8027 | 0.9794 |
|
| 89 |
+
| 0.0012 | 18.0653 | 15500 | 0.1430 | 0.8002 | 0.8119 | 0.8060 | 0.9798 |
|
| 90 |
+
| 0.0009 | 18.6480 | 16000 | 0.1558 | 0.7855 | 0.8166 | 0.8007 | 0.9788 |
|
| 91 |
+
| 0.0014 | 19.2308 | 16500 | 0.1478 | 0.8012 | 0.8119 | 0.8065 | 0.9797 |
|
| 92 |
+
| 0.001 | 19.8135 | 17000 | 0.1498 | 0.8101 | 0.8087 | 0.8094 | 0.9798 |
|
| 93 |
+
| 0.0009 | 20.3963 | 17500 | 0.1515 | 0.7946 | 0.8116 | 0.8030 | 0.9795 |
|
| 94 |
+
| 0.0008 | 20.9790 | 18000 | 0.1546 | 0.7967 | 0.8165 | 0.8065 | 0.9796 |
|
| 95 |
+
| 0.0009 | 21.5618 | 18500 | 0.1553 | 0.7953 | 0.8162 | 0.8056 | 0.9796 |
|
| 96 |
+
| 0.0008 | 22.1445 | 19000 | 0.1540 | 0.8001 | 0.8103 | 0.8052 | 0.9798 |
|
| 97 |
+
| 0.0006 | 22.7273 | 19500 | 0.1620 | 0.7877 | 0.8208 | 0.8039 | 0.9793 |
|
| 98 |
+
| 0.0007 | 23.3100 | 20000 | 0.1605 | 0.8127 | 0.7999 | 0.8062 | 0.9795 |
|
| 99 |
+
| 0.0005 | 23.8928 | 20500 | 0.1589 | 0.7974 | 0.8132 | 0.8052 | 0.9799 |
|
| 100 |
+
| 0.0005 | 24.4755 | 21000 | 0.1593 | 0.8016 | 0.8093 | 0.8054 | 0.9797 |
|
| 101 |
+
| 0.0006 | 25.0583 | 21500 | 0.1561 | 0.8060 | 0.8114 | 0.8087 | 0.9800 |
|
| 102 |
+
| 0.0005 | 25.6410 | 22000 | 0.1587 | 0.8028 | 0.8152 | 0.8089 | 0.9798 |
|
| 103 |
+
| 0.0004 | 26.2238 | 22500 | 0.1582 | 0.8058 | 0.8101 | 0.8080 | 0.9802 |
|
| 104 |
+
| 0.0004 | 26.8065 | 23000 | 0.1612 | 0.8003 | 0.8162 | 0.8081 | 0.9799 |
|
| 105 |
+
| 0.0003 | 27.3893 | 23500 | 0.1609 | 0.8066 | 0.8142 | 0.8104 | 0.9801 |
|
| 106 |
+
| 0.0003 | 27.9720 | 24000 | 0.1627 | 0.8032 | 0.8178 | 0.8104 | 0.9801 |
|
| 107 |
+
| 0.0003 | 28.5548 | 24500 | 0.1616 | 0.8081 | 0.8127 | 0.8104 | 0.9801 |
|
| 108 |
+
| 0.0003 | 29.1375 | 25000 | 0.1627 | 0.8065 | 0.8153 | 0.8109 | 0.9801 |
|
| 109 |
+
| 0.0002 | 29.7203 | 25500 | 0.1624 | 0.8067 | 0.8152 | 0.8109 | 0.9801 |
|
| 110 |
|
| 111 |
|
| 112 |
### Framework versions
|
config.json
CHANGED
|
@@ -34,7 +34,7 @@
|
|
| 34 |
"max_position_embeddings": 514,
|
| 35 |
"model_type": "xlm-roberta",
|
| 36 |
"num_attention_heads": 12,
|
| 37 |
-
"num_hidden_layers":
|
| 38 |
"output_past": true,
|
| 39 |
"pad_token_id": 1,
|
| 40 |
"position_embedding_type": "absolute",
|
|
|
|
| 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",
|
eval_result_ner.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"ceb_gja": {"precision": 0.
|
|
|
|
| 1 |
+
{"ceb_gja": {"precision": 0.5352112676056338, "recall": 0.7755102040816326, "f1": 0.6333333333333333, "accuracy": 0.9621621621621622}, "en_pud": {"precision": 0.7788649706457925, "recall": 0.7404651162790697, "f1": 0.7591797806390082, "accuracy": 0.9763411409142425}, "de_pud": {"precision": 0.7080568720379147, "recall": 0.7189605389797883, "f1": 0.7134670487106017, "accuracy": 0.9686371946931696}, "pt_pud": {"precision": 0.8005671077504726, "recall": 0.7707006369426752, "f1": 0.7853500231803432, "accuracy": 0.9794933139659077}, "ru_pud": {"precision": 0.6657433056325023, "recall": 0.6959459459459459, "f1": 0.6805096743747051, "accuracy": 0.9683802634978042}, "sv_pud": {"precision": 0.8348439073514602, "recall": 0.8056365403304179, "f1": 0.8199802176063304, "accuracy": 0.9818096036905012}, "tl_trg": {"precision": 0.6551724137931034, "recall": 0.8260869565217391, "f1": 0.7307692307692308, "accuracy": 0.9795640326975477}, "tl_ugnayan": {"precision": 0.525, "recall": 0.6363636363636364, "f1": 0.5753424657534246, "accuracy": 0.968094804010939}, "zh_gsd": {"precision": 0.8333333333333334, "recall": 0.8279009126466753, "f1": 0.8306082406801831, "accuracy": 0.9773559773559773}, "zh_gsdsimp": {"precision": 0.8095238095238095, "recall": 0.8020969855832241, "f1": 0.8057932850559578, "accuracy": 0.9738594738594739}, "hr_set": {"precision": 0.895438596491228, "recall": 0.909479686386315, "f1": 0.9024045261669025, "accuracy": 0.987881286067601}, "da_ddt": {"precision": 0.8062953995157385, "recall": 0.7449664429530202, "f1": 0.7744186046511627, "accuracy": 0.9834380923875087}, "en_ewt": {"precision": 0.784390243902439, "recall": 0.7389705882352942, "f1": 0.7610033128253668, "accuracy": 0.9764912140893334}, "pt_bosque": {"precision": 0.7774621212121212, "recall": 0.6757201646090535, "f1": 0.7230295024218406, "accuracy": 0.9735907839443559}, "sr_set": {"precision": 0.9101654846335697, "recall": 0.9090909090909091, "f1": 0.9096278795038394, "accuracy": 0.9887925750809912}, "sk_snk": {"precision": 0.7014428412874584, "recall": 0.6907103825136612, "f1": 0.6960352422907489, "accuracy": 0.9594849246231156}, "sv_talbanken": {"precision": 0.7897196261682243, "recall": 0.8622448979591837, "f1": 0.824390243902439, "accuracy": 0.9967119791922265}}
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:23c7273a5f1b1b96fe9fc6f74550f48f40e96438ab000fb0fc5884d7c7619c96
|
| 3 |
+
size 939737140
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5304
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:85d2fea155044c94b83968889b9ddd0016d3b66b5afd13b309fbf06c4b382380
|
| 3 |
size 5304
|