librarian-bot commited on
Commit
39f0618
1 Parent(s): a60a40c

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-multilingual-cased`](https://huggingface.co/bert-base-multilingual-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). Your input is invaluable to us!

Files changed (1) hide show
  1. README.md +10 -9
README.md CHANGED
@@ -9,29 +9,30 @@ metrics:
9
  - recall
10
  - f1
11
  - accuracy
 
12
  model-index:
13
  - name: mbert-finetuned-ner
14
  results:
15
  - task:
16
- name: Token Classification
17
  type: token-classification
 
18
  dataset:
19
  name: wikiann
20
  type: wikiann
21
  args: lv
22
  metrics:
23
- - name: Precision
24
- type: precision
25
  value: 0.9304986338797814
26
- - name: Recall
27
- type: recall
28
  value: 0.9375430144528561
29
- - name: F1
30
- type: f1
31
  value: 0.9340075419952005
32
- - name: Accuracy
33
- type: accuracy
34
  value: 0.9699674740348558
 
35
  ---
36
 
37
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
9
  - recall
10
  - f1
11
  - accuracy
12
+ base_model: bert-base-multilingual-cased
13
  model-index:
14
  - name: mbert-finetuned-ner
15
  results:
16
  - task:
 
17
  type: token-classification
18
+ name: Token Classification
19
  dataset:
20
  name: wikiann
21
  type: wikiann
22
  args: lv
23
  metrics:
24
+ - type: precision
 
25
  value: 0.9304986338797814
26
+ name: Precision
27
+ - type: recall
28
  value: 0.9375430144528561
29
+ name: Recall
30
+ - type: f1
31
  value: 0.9340075419952005
32
+ name: F1
33
+ - type: accuracy
34
  value: 0.9699674740348558
35
+ name: Accuracy
36
  ---
37
 
38
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You