Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`cardiffnlp/twitter-roberta-base-2019-90m`](https://huggingface.co/cardiffnlp/twitter-roberta-base-2019-90m) 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!
@@ -4,6 +4,16 @@ datasets:
|
|
4 |
metrics:
|
5 |
- f1
|
6 |
- accuracy
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
7 |
model-index:
|
8 |
- name: cardiffnlp/twitter-roberta-base-2019-90m-tweet-topic-multi-all
|
9 |
results:
|
@@ -13,24 +23,18 @@ model-index:
|
|
13 |
dataset:
|
14 |
name: cardiffnlp/tweet_topic_multi
|
15 |
type: cardiffnlp/tweet_topic_multi
|
|
|
16 |
args: cardiffnlp/tweet_topic_multi
|
17 |
-
split: test_2021
|
18 |
metrics:
|
19 |
-
-
|
20 |
-
type: f1
|
21 |
value: 0.7625128733264676
|
22 |
-
|
23 |
-
|
24 |
value: 0.6035334168546909
|
25 |
-
|
26 |
-
|
27 |
value: 0.547945205479452
|
28 |
-
|
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/twitter-roberta-base-2019-90m-tweet-topic-multi-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: cardiffnlp/twitter-roberta-base-2019-90m
|
17 |
model-index:
|
18 |
- name: cardiffnlp/twitter-roberta-base-2019-90m-tweet-topic-multi-all
|
19 |
results:
|
|
|
23 |
dataset:
|
24 |
name: cardiffnlp/tweet_topic_multi
|
25 |
type: cardiffnlp/tweet_topic_multi
|
26 |
+
split: test_2021
|
27 |
args: cardiffnlp/tweet_topic_multi
|
|
|
28 |
metrics:
|
29 |
+
- type: f1
|
|
|
30 |
value: 0.7625128733264676
|
31 |
+
name: F1
|
32 |
+
- type: f1_macro
|
33 |
value: 0.6035334168546909
|
34 |
+
name: F1 (macro)
|
35 |
+
- type: accuracy
|
36 |
value: 0.547945205479452
|
37 |
+
name: Accuracy
|
|
|
|
|
|
|
|
|
|
|
38 |
---
|
39 |
# cardiffnlp/twitter-roberta-base-2019-90m-tweet-topic-multi-all
|
40 |
|