Hugging Face's logo

AIventurer
/
bert-finetuned-ner

Token Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
1
bert-finetuned-ner
File size: 4,465 Bytes 
1aa0e8e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fb042dc
1aa0e8e
 
 
 
 
 
 
fb042dc
1aa0e8e
fb042dc
 
1aa0e8e
fb042dc
 
1aa0e8e
fb042dc
 
1aa0e8e
fb042dc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1aa0e8e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
 
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
  results:
  - task:
      type: token-classification
      name: Token Classification
    dataset:
      name: conll2003
      type: conll2003
      config: conll2003
      split: validation
      args: conll2003
    metrics:
    - type: precision
      value: 0.9316493313521546
      name: Precision
    - type: recall
      value: 0.9496802423426456
      name: Recall
    - type: f1
      value: 0.9405783815317944
      name: F1
    - type: accuracy
      value: 0.9861806087007712
      name: Accuracy
  - task:
      type: token-classification
      name: Token Classification
    dataset:
      name: conll2003
      type: conll2003
      config: conll2003
      split: test
    metrics:
    - type: accuracy
      value: 0.8996864215817588
      name: Accuracy
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWJkMzFiYTc0YzI3MGRiOGQ0MTA0OTgwYmQ3ODU2ZTk5MGQ5NGQwYjViMzhiZWFjNzUyMmYxM2QxOTQ5ZTI0MyIsInZlcnNpb24iOjF9.SECjYrUHXW-IJZPqjPMM15PAItaCHQKynFjkmu3cXj2wvUh-O_mvAvaqq3fLJSyNQfPyImRc89_gusSsgGD8Aw
    - type: precision
      value: 0.9290522347872914
      name: Precision
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTdhNzkwYTMzYzE0NzdkNzc0ODQ4NmYwNTVjOGI1ZGQ3YmZlNmJjNzEwNDFiOWZiMGMxYTM1YTIxNGVkMTc2NyIsInZlcnNpb24iOjF9.imy5h8_PQmOLSWZx341f_VdLqaXSUfgmnvBtq8r5l-tc9BbzUqdl5TiyxLyqOt0JFO0lQooirG1YxivynmesBw
    - type: recall
      value: 0.9153430381006068
      name: Recall
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzY5M2E3ZDc4NWFkNGFkOWY1Mzk3YzIyYzg0Y2U0NzM1ZWRkNjczM2QyODdkMTg5MDhlZDMwOThhMTA3NGFlYSIsInZlcnNpb24iOjF9.8aVjcW3T8W4a9LiEAgakRM_kechC9xK51nAl3SxypmES6MNxVjsYCD8wvxPF7ddgmTCB0vyCTeelgT6HuGhtCQ
    - type: auc
      value: NaN
      name: AUC
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmQ0ZTk4ZWJmNmU4M2U1OTNiZGMyNmNmYmJmMzMwZjQ4MDRlYmYxOWJjNTM0N2FjMWExNGI1ZTVmN2I2MGZhOSIsInZlcnNpb24iOjF9.0B6-aHCUx_SdHfSTlcXlVh8mE3gQe7L2Dk2-RyLp7a3YUzOhJNAj--Bz0I5lGH0m7PffPwBuZpccdnFJfg_WAg
    - type: f1
      value: 0.9221466869331375
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDk1ZWY1MTVhYTZmYzNhYmZkNjdiNjNjMTk0OGMzNzQzMmE0MGI4NTc5YmViZTg3NDQ2MjE1YzNkZDUwZTc4NSIsInZlcnNpb24iOjF9.ZlDFXSg8DZL3KLeU3liwZYWgpF1wrTieUYTVg9lVkgYb7A5jlCcgT4X3LqXCScaIt84BS_6-eqNHV_ukJiUUAQ
    - type: loss
      value: 0.8573787212371826
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjY0OWJmZWI5ZTA5ODIzYzE5YmFkZmQ2OTIwOTJlNDU4ZmUyZDFlYTU1MmRjODRlMWZlMmMyYjUwNmQyYzhmNCIsInZlcnNpb24iOjF9.mCnEvOsb3-HlTzhiY7kboe1rCD8ikdyKgEPMixST1qbGoTmfff0ZclZL9Sjz46MREnLYNgPr_whSEzvMWC3aAw
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-finetuned-ner

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0630
- Precision: 0.9316
- Recall: 0.9497
- F1: 0.9406
- Accuracy: 0.9862

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0885        | 1.0   | 1756 | 0.0692          | 0.9162    | 0.9312 | 0.9236 | 0.9813   |
| 0.0364        | 2.0   | 3512 | 0.0652          | 0.9233    | 0.9455 | 0.9342 | 0.9854   |
| 0.018         | 3.0   | 5268 | 0.0630          | 0.9316    | 0.9497 | 0.9406 | 0.9862   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3