librarian-bot commited on
Commit
d7b0693
1 Parent(s): ec2ab04

Librarian Bot: Add base_model information to model

Browse files

This pull request aims to enrich the metadata of your model by adding [`bert-base-cased`](https://huggingface.co/bert-base-cased) as a `base_model` field, situated in the `YAML` block of your model's `README.md`.

How did we find this information? We performed a regular expression match on your `README.md` file to determine the connection.

**Why add this?** Enhancing your model's metadata in this way:
- **Boosts Discoverability** - It becomes straightforward to trace the relationships between various models on the Hugging Face Hub.
- **Highlights Impact** - It showcases the contributions and influences different models have within the community.

For a hands-on example of how such metadata can play a pivotal role in mapping model connections, take a look at [librarian-bots/base_model_explorer](https://huggingface.co/spaces/librarian-bots/base_model_explorer).

This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bot). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to [@davanstrien](https://huggingface.co/davanstrien).

If you want to automatically add `base_model` metadata to more of your modes you can use the [Librarian Bot](https://huggingface.co/librarian-bot) [Metadata Request Service](https://huggingface.co/spaces/librarian-bots/metadata_request_service)!

Files changed (1) hide show
  1. README.md +20 -19
README.md CHANGED
@@ -9,29 +9,30 @@ metrics:
9
  - recall
10
  - f1
11
  - accuracy
 
12
  model-index:
13
  - name: bert-base-cased-ner-conll2003
14
  results:
15
  - task:
16
- name: Token Classification
17
  type: token-classification
 
18
  dataset:
19
  name: conll2003
20
  type: conll2003
21
  args: conll2003
22
  metrics:
23
- - name: Precision
24
- type: precision
25
  value: 0.9438052359513089
26
- - name: Recall
27
- type: recall
28
  value: 0.9525412319084483
29
- - name: F1
30
- type: f1
31
  value: 0.9481531116508919
32
- - name: Accuracy
33
- type: accuracy
34
  value: 0.9910634321093416
 
35
  - task:
36
  type: token-classification
37
  name: Token Classification
@@ -41,25 +42,25 @@ model-index:
41
  config: conll2003
42
  split: test
43
  metrics:
44
- - name: Accuracy
45
- type: accuracy
46
  value: 0.9116307653519484
 
47
  verified: true
48
- - name: Precision
49
- type: precision
50
  value: 0.9366103911345081
 
51
  verified: true
52
- - name: Recall
53
- type: recall
54
  value: 0.9262526113340186
 
55
  verified: true
56
- - name: F1
57
- type: f1
58
  value: 0.9314027058794109
 
59
  verified: true
60
- - name: loss
61
- type: loss
62
  value: 0.4366346299648285
 
63
  verified: true
64
  ---
65
 
 
9
  - recall
10
  - f1
11
  - accuracy
12
+ base_model: bert-base-cased
13
  model-index:
14
  - name: bert-base-cased-ner-conll2003
15
  results:
16
  - task:
 
17
  type: token-classification
18
+ name: Token Classification
19
  dataset:
20
  name: conll2003
21
  type: conll2003
22
  args: conll2003
23
  metrics:
24
+ - type: precision
 
25
  value: 0.9438052359513089
26
+ name: Precision
27
+ - type: recall
28
  value: 0.9525412319084483
29
+ name: Recall
30
+ - type: f1
31
  value: 0.9481531116508919
32
+ name: F1
33
+ - type: accuracy
34
  value: 0.9910634321093416
35
+ name: Accuracy
36
  - task:
37
  type: token-classification
38
  name: Token Classification
 
42
  config: conll2003
43
  split: test
44
  metrics:
45
+ - type: accuracy
 
46
  value: 0.9116307653519484
47
+ name: Accuracy
48
  verified: true
49
+ - type: precision
 
50
  value: 0.9366103911345081
51
+ name: Precision
52
  verified: true
53
+ - type: recall
 
54
  value: 0.9262526113340186
55
+ name: Recall
56
  verified: true
57
+ - type: f1
 
58
  value: 0.9314027058794109
59
+ name: F1
60
  verified: true
61
+ - type: loss
 
62
  value: 0.4366346299648285
63
+ name: loss
64
  verified: true
65
  ---
66