Hugging Face's logo

manibt1993
/
huner_ncbi_disease_dslim

Token Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Model card Files
xet
 Metrics Community
manibt1993 commited on
Commit
47fc0f6
·
verified ·
1 Parent(s): 0d5651d

Training complete

Browse files
Files changed (2) hide show
  1. README.md +109 -0
  2. runs/Feb06_05-04-58_0fc676717a2f/events.out.tfevents.1707195906.0fc676717a2f.1788.0 +2 -2
README.md ADDED
@@ -0,0 +1,109 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: dslim/distilbert-NER
4
+ tags:
5
+ - generated_from_trainer
6
+ datasets:
7
+ - transformer_dataset_ner
8
+ metrics:
9
+ - precision
10
+ - recall
11
+ - f1
12
+ - accuracy
13
+ model-index:
14
+ - name: huner_ncbi_disease_dslim
15
+ results:
16
+ - task:
17
+ name: Token Classification
18
+ type: token-classification
19
+ dataset:
20
+ name: transformer_dataset_ner
21
+ type: transformer_dataset_ner
22
+ config: ncbi_disease
23
+ split: validation
24
+ args: ncbi_disease
25
+ metrics:
26
+ - name: Precision
27
+ type: precision
28
+ value: 0.8325183374083129
29
+ - name: Recall
30
+ type: recall
31
+ value: 0.8653113087674714
32
+ - name: F1
33
+ type: f1
34
+ value: 0.8485981308411215
35
+ - name: Accuracy
36
+ type: accuracy
37
+ value: 0.9849891909996041
38
+ ---
39
+
40
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
41
+ should probably proofread and complete it, then remove this comment. -->
42
+
43
+ # huner_ncbi_disease_dslim
44
+
45
+ This model is a fine-tuned version of [dslim/distilbert-NER](https://huggingface.co/dslim/distilbert-NER) on the transformer_dataset_ner dataset.
46
+ It achieves the following results on the evaluation set:
47
+ - Loss: 0.1484
48
+ - Precision: 0.8325
49
+ - Recall: 0.8653
50
+ - F1: 0.8486
51
+ - Accuracy: 0.9850
52
+
53
+ ## Model description
54
+
55
+ More information needed
56
+
57
+ ## Intended uses & limitations
58
+
59
+ More information needed
60
+
61
+ ## Training and evaluation data
62
+
63
+ More information needed
64
+
65
+ ## Training procedure
66
+
67
+ ### Training hyperparameters
68
+
69
+ The following hyperparameters were used during training:
70
+ - learning_rate: 2e-05
71
+ - train_batch_size: 8
72
+ - eval_batch_size: 8
73
+ - seed: 42
74
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
75
+ - lr_scheduler_type: linear
76
+ - num_epochs: 20
77
+
78
+ ### Training results
79
+
80
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
81
+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
82
+ | 0.1243 | 1.0 | 667 | 0.0669 | 0.7013 | 0.8412 | 0.7649 | 0.9787 |
83
+ | 0.0512 | 2.0 | 1334 | 0.0656 | 0.7825 | 0.8412 | 0.8108 | 0.9818 |
84
+ | 0.0221 | 3.0 | 2001 | 0.0744 | 0.7908 | 0.8501 | 0.8194 | 0.9822 |
85
+ | 0.0107 | 4.0 | 2668 | 0.1022 | 0.7940 | 0.8475 | 0.8199 | 0.9808 |
86
+ | 0.008 | 5.0 | 3335 | 0.1055 | 0.7818 | 0.8602 | 0.8191 | 0.9816 |
87
+ | 0.0057 | 6.0 | 4002 | 0.1173 | 0.8067 | 0.8590 | 0.832 | 0.9830 |
88
+ | 0.0027 | 7.0 | 4669 | 0.1188 | 0.8188 | 0.8501 | 0.8342 | 0.9834 |
89
+ | 0.0022 | 8.0 | 5336 | 0.1229 | 0.8080 | 0.8450 | 0.8261 | 0.9826 |
90
+ | 0.0019 | 9.0 | 6003 | 0.1341 | 0.8007 | 0.8526 | 0.8258 | 0.9834 |
91
+ | 0.0019 | 10.0 | 6670 | 0.1360 | 0.8045 | 0.8628 | 0.8326 | 0.9822 |
92
+ | 0.0011 | 11.0 | 7337 | 0.1376 | 0.8163 | 0.8640 | 0.8395 | 0.9838 |
93
+ | 0.0008 | 12.0 | 8004 | 0.1447 | 0.8007 | 0.8577 | 0.8282 | 0.9833 |
94
+ | 0.0006 | 13.0 | 8671 | 0.1381 | 0.8139 | 0.8615 | 0.8370 | 0.9839 |
95
+ | 0.0005 | 14.0 | 9338 | 0.1398 | 0.8297 | 0.8666 | 0.8477 | 0.9843 |
96
+ | 0.0004 | 15.0 | 10005 | 0.1404 | 0.8232 | 0.8640 | 0.8431 | 0.9842 |
97
+ | 0.0003 | 16.0 | 10672 | 0.1486 | 0.8329 | 0.8551 | 0.8439 | 0.9838 |
98
+ | 0.0 | 17.0 | 11339 | 0.1469 | 0.8114 | 0.8691 | 0.8393 | 0.9837 |
99
+ | 0.0002 | 18.0 | 12006 | 0.1500 | 0.8297 | 0.8602 | 0.8447 | 0.9843 |
100
+ | 0.0001 | 19.0 | 12673 | 0.1489 | 0.8315 | 0.8653 | 0.8481 | 0.9849 |
101
+ | 0.0 | 20.0 | 13340 | 0.1484 | 0.8325 | 0.8653 | 0.8486 | 0.9850 |
102
+
103
+
104
+ ### Framework versions
105
+
106
+ - Transformers 4.35.2
107
+ - Pytorch 2.1.0+cu121
108
+ - Datasets 2.16.1
109
+ - Tokenizers 0.15.1
runs/Feb06_05-04-58_0fc676717a2f/events.out.tfevents.1707195906.0fc676717a2f.1788.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:5b9d9af7aeeb2607b8dec2f4bac9c40a5cf431c250511c99746b262ddcc9b6b6
3
- size 17370
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4c6d0d9eeeaa84f0f9738cf6bdaa507ba847422c58eaeccb21a87ba10937e7d3
3
+ size 18196