librarian-bot commited on
Commit
aec445f
1 Parent(s): db6d0eb

Librarian Bot: Add base_model information to model

Browse files

This pull request aims to enrich the metadata of your model by adding [`roberta-base`](https://huggingface.co/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). Your input is invaluable to us!

Files changed (1) hide show
  1. README.md +17 -13
README.md CHANGED
@@ -4,6 +4,16 @@ datasets:
4
  metrics:
5
  - f1
6
  - accuracy
 
 
 
 
 
 
 
 
 
 
7
  model-index:
8
  - name: cardiffnlp/roberta-base-tweet-topic-single-all
9
  results:
@@ -13,24 +23,18 @@ model-index:
13
  dataset:
14
  name: cardiffnlp/tweet_topic_single
15
  type: cardiffnlp/tweet_topic_single
 
16
  args: cardiffnlp/tweet_topic_single
17
- split: test_2021
18
  metrics:
19
- - name: F1
20
- type: f1
21
  value: 0.8877731836975783
22
- - name: F1 (macro)
23
- type: f1_macro
24
  value: 0.7979301633555328
25
- - name: Accuracy
26
- type: accuracy
27
  value: 0.8877731836975783
28
- pipeline_tag: text-classification
29
- widget:
30
- - text: "I'm sure the {@Tampa Bay Lightning@} would’ve rather faced the Flyers but man does their experience versus the Blue Jackets this year and last help them a lot versus this Islanders team. Another meat grinder upcoming for the good guys"
31
- example_title: "Example 1"
32
- - text: "Love to take night time bike rides at the jersey shore. Seaside Heights boardwalk. Beautiful weather. Wishing everyone a safe Labor Day weekend in the US."
33
- example_title: "Example 2"
34
  ---
35
  # cardiffnlp/roberta-base-tweet-topic-single-all
36
 
 
4
  metrics:
5
  - f1
6
  - accuracy
7
+ pipeline_tag: text-classification
8
+ widget:
9
+ - text: I'm sure the {@Tampa Bay Lightning@} would’ve rather faced the Flyers but
10
+ man does their experience versus the Blue Jackets this year and last help them
11
+ a lot versus this Islanders team. Another meat grinder upcoming for the good guys
12
+ example_title: Example 1
13
+ - text: Love to take night time bike rides at the jersey shore. Seaside Heights boardwalk.
14
+ Beautiful weather. Wishing everyone a safe Labor Day weekend in the US.
15
+ example_title: Example 2
16
+ base_model: roberta-base
17
  model-index:
18
  - name: cardiffnlp/roberta-base-tweet-topic-single-all
19
  results:
 
23
  dataset:
24
  name: cardiffnlp/tweet_topic_single
25
  type: cardiffnlp/tweet_topic_single
26
+ split: test_2021
27
  args: cardiffnlp/tweet_topic_single
 
28
  metrics:
29
+ - type: f1
 
30
  value: 0.8877731836975783
31
+ name: F1
32
+ - type: f1_macro
33
  value: 0.7979301633555328
34
+ name: F1 (macro)
35
+ - type: accuracy
36
  value: 0.8877731836975783
37
+ name: Accuracy
 
 
 
 
 
38
  ---
39
  # cardiffnlp/roberta-base-tweet-topic-single-all
40