Hugging Face's logo

ocm
/
bert-finetuned-ner

Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
2
ocm commited on
Commit
f78ecf5
·
1 Parent(s): 32b67ac

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +12 -12
README.md CHANGED
@@ -24,16 +24,16 @@ model-index:
24
  metrics:
25
  - name: Precision
26
  type: precision
27
- value: 0.9352970378950852
28
  - name: Recall
29
  type: recall
30
- value: 0.9511948838774823
31
  - name: F1
32
  type: f1
33
- value: 0.9431789737171463
34
  - name: Accuracy
35
  type: accuracy
36
- value: 0.9866368399364219
37
  ---
38
 
39
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,10 +43,10 @@ should probably proofread and complete it, then remove this comment. -->
43
 
44
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
45
  It achieves the following results on the evaluation set:
46
- - Loss: 0.0612
47
- - Precision: 0.9353
48
- - Recall: 0.9512
49
- - F1: 0.9432
50
  - Accuracy: 0.9866
51
 
52
  ## Model description
@@ -78,14 +78,14 @@ The following hyperparameters were used during training:
78
 
79
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
80
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
81
- | 0.0876 | 1.0 | 1756 | 0.0698 | 0.9163 | 0.9307 | 0.9234 | 0.9817 |
82
- | 0.0347 | 2.0 | 3512 | 0.0643 | 0.9253 | 0.9478 | 0.9364 | 0.9857 |
83
- | 0.0191 | 3.0 | 5268 | 0.0612 | 0.9353 | 0.9512 | 0.9432 | 0.9866 |
84
 
85
 
86
  ### Framework versions
87
 
88
- - Transformers 4.27.1
89
  - Pytorch 1.13.1+cu116
90
  - Datasets 2.10.1
91
  - Tokenizers 0.13.2
 
24
  metrics:
25
  - name: Precision
26
  type: precision
27
+ value: 0.9328493647912885
28
  - name: Recall
29
  type: recall
30
+ value: 0.9515314708852238
31
  - name: F1
32
  type: f1
33
+ value: 0.942097808881113
34
  - name: Accuracy
35
  type: accuracy
36
+ value: 0.9865632542532525
37
  ---
38
 
39
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
43
 
44
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
45
  It achieves the following results on the evaluation set:
46
+ - Loss: 0.0591
47
+ - Precision: 0.9328
48
+ - Recall: 0.9515
49
+ - F1: 0.9421
50
  - Accuracy: 0.9866
51
 
52
  ## Model description
 
78
 
79
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
80
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
81
+ | 0.088 | 1.0 | 1756 | 0.0673 | 0.9190 | 0.9334 | 0.9261 | 0.9823 |
82
+ | 0.0346 | 2.0 | 3512 | 0.0611 | 0.9284 | 0.9477 | 0.9380 | 0.9855 |
83
+ | 0.0178 | 3.0 | 5268 | 0.0591 | 0.9328 | 0.9515 | 0.9421 | 0.9866 |
84
 
85
 
86
  ### Framework versions
87
 
88
+ - Transformers 4.27.3
89
  - Pytorch 1.13.1+cu116
90
  - Datasets 2.10.1
91
  - Tokenizers 0.13.2