librarian-bot commited on
Commit
1217a4c
1 Parent(s): efb7c0d

Librarian Bot: Add base_model information to model

Browse files

This pull request aims to enrich the metadata of your model by adding [`xlm-roberta-base`](https://huggingface.co/xlm-roberta-base) 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 +4 -3
README.md CHANGED
@@ -7,12 +7,13 @@ datasets:
7
  - xnli
8
  metrics:
9
  - accuracy
 
10
  model-index:
11
  - name: xnli_xlm_r_only_sw
12
  results:
13
  - task:
14
- name: Text Classification
15
  type: text-classification
 
16
  dataset:
17
  name: xnli
18
  type: xnli
@@ -20,9 +21,9 @@ model-index:
20
  split: train
21
  args: sw
22
  metrics:
23
- - name: Accuracy
24
- type: accuracy
25
  value: 0.6903614457831325
 
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
7
  - xnli
8
  metrics:
9
  - accuracy
10
+ base_model: xlm-roberta-base
11
  model-index:
12
  - name: xnli_xlm_r_only_sw
13
  results:
14
  - task:
 
15
  type: text-classification
16
+ name: Text Classification
17
  dataset:
18
  name: xnli
19
  type: xnli
 
21
  split: train
22
  args: sw
23
  metrics:
24
+ - type: accuracy
 
25
  value: 0.6903614457831325
26
+ name: Accuracy
27
  ---
28
 
29
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You