librarian-bot commited on
Commit
49a3066
1 Parent(s): c56b802

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 +10 -9
README.md CHANGED
@@ -9,12 +9,13 @@ metrics:
9
  - recall
10
  - f1
11
  - accuracy
 
12
  model-index:
13
  - name: bert-finetuned-ner
14
  results:
15
  - task:
16
- name: Token Classification
17
  type: token-classification
 
18
  dataset:
19
  name: conll2003
20
  type: conll2003
@@ -22,18 +23,18 @@ model-index:
22
  split: train
23
  args: conll2003
24
  metrics:
25
- - name: Precision
26
- type: precision
27
  value: 0.9371173258315406
28
- - name: Recall
29
- type: recall
30
  value: 0.9530461124200605
31
- - name: F1
32
- type: f1
33
  value: 0.945014601585315
34
- - name: Accuracy
35
- type: accuracy
36
  value: 0.9865338199799847
 
37
  ---
38
 
39
  <!-- 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-cased
13
  model-index:
14
  - name: bert-finetuned-ner
15
  results:
16
  - task:
 
17
  type: token-classification
18
+ name: Token Classification
19
  dataset:
20
  name: conll2003
21
  type: conll2003
 
23
  split: train
24
  args: conll2003
25
  metrics:
26
+ - type: precision
 
27
  value: 0.9371173258315406
28
+ name: Precision
29
+ - type: recall
30
  value: 0.9530461124200605
31
+ name: Recall
32
+ - type: f1
33
  value: 0.945014601585315
34
+ name: F1
35
+ - type: accuracy
36
  value: 0.9865338199799847
37
+ name: Accuracy
38
  ---
39
 
40
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You