File size: 3,258 Bytes
bf420e2 a516094 bf420e2 a516094 bf420e2 a516094 bf420e2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
---
datasets:
- tweet_eval
metrics:
- f1
- accuracy
model-index:
- name: cardiffnlp/twitter-roberta-base-2021-124m-sentiment
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: tweet_eval
type: sentiment
split: test
metrics:
- name: Micro F1 (tweet_eval/sentiment)
type: micro_f1_tweet_eval/sentiment
value: 0.7133669814392706
- name: Macro F1 (tweet_eval/sentiment)
type: micro_f1_tweet_eval/sentiment
value: 0.7158353597305398
- name: Accuracy (tweet_eval/sentiment)
type: accuracy_tweet_eval/sentiment
value: 0.7133669814392706
pipeline_tag: text-classification
widget:
- text: Get the all-analog Classic Vinyl Edition of "Takin Off" Album from {@herbiehancock@} via {@bluenoterecords@} link below {{URL}}
example_title: "topic_classification 1"
- text: Yes, including Medicare and social security saving👍
example_title: "sentiment 1"
- text: All two of them taste like ass.
example_title: "offensive 1"
- text: If you wanna look like a badass, have drama on social media
example_title: "irony 1"
- text: Whoever just unfollowed me you a bitch
example_title: "hate 1"
- text: I love swimming for the same reason I love meditating...the feeling of weightlessness.
example_title: "emotion 1"
- text: Beautiful sunset last night from the pontoon @TupperLakeNY
example_title: "emoji 1"
---
# cardiffnlp/twitter-roberta-base-2021-124m-sentiment
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-2021-124m](https://huggingface.co/cardiffnlp/twitter-roberta-base-2021-124m) on the
[`tweet_eval (sentiment)`](https://huggingface.co/datasets/tweet_eval)
via [`tweetnlp`](https://github.com/cardiffnlp/tweetnlp).
Training split is `train` and parameters have been tuned on the validation split `validation`.
Following metrics are achieved on the test split `test` ([link](https://huggingface.co/cardiffnlp/twitter-roberta-base-2021-124m-sentiment/raw/main/metric.json)).
- F1 (micro): 0.7133669814392706
- F1 (macro): 0.7158353597305398
- Accuracy: 0.7133669814392706
### Usage
Install tweetnlp via pip.
```shell
pip install tweetnlp
```
Load the model in python.
```python
import tweetnlp
model = tweetnlp.Classifier("cardiffnlp/twitter-roberta-base-2021-124m-sentiment", max_length=128)
model.predict('Get the all-analog Classic Vinyl Edition of "Takin Off" Album from {@herbiehancock@} via {@bluenoterecords@} link below {{URL}}')
```
### Reference
```
@inproceedings{camacho-collados-etal-2022-tweetnlp,
title={{T}weet{NLP}: {C}utting-{E}dge {N}atural {L}anguage {P}rocessing for {S}ocial {M}edia},
author={Camacho-Collados, Jose and Rezaee, Kiamehr and Riahi, Talayeh and Ushio, Asahi and Loureiro, Daniel and Antypas, Dimosthenis and Boisson, Joanne and Espinosa-Anke, Luis and Liu, Fangyu and Mart{'\i}nez-C{'a}mara, Eugenio and others},
author = "Ushio, Asahi and
Camacho-Collados, Jose",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = nov,
year = "2022",
address = "Abu Dhabi, U.A.E.",
publisher = "Association for Computational Linguistics",
}
```
|