File size: 3,180 Bytes
7352fe8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
88
89
---
model-index:
- name: poltextlab/illframes-climate-v5
  results:
  - task:
      type: text-classification
    metrics:
    - name: Accuracy
      type: accuracy
      value: 72%
    - name: F1-Score
      type: f1
      value: 64%
tags:
- text-classification
- pytorch
metrics:
- precision
- recall
- f1-score
language:
- en
base_model:
- xlm-roberta-large
pipeline_tag: text-classification
library_name: transformers
license: cc-by-4.0
extra_gated_prompt: Our models are intended for academic use only. If you are not
  affiliated with an academic institution, please provide a rationale for using our
  models. Please allow us a few business days to manually review subscriptions.
extra_gated_fields:
  Name: text
  Country: country
  Institution: text
  Institution Email: text
  Please specify your academic use case: text
---

# illframes-climate-v5


# How to use the model

```python
from transformers import AutoTokenizer, pipeline

tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-large")
pipe = pipeline(
    model="poltextlab/illframes-climate-v5",
    task="text-classification",
    tokenizer=tokenizer,
    use_fast=False,
    token="<your_hf_read_only_token>"
)

text = "<text_to_classify>"
pipe(text)
```
        

# Classification Report

## Overall Performance:

* **Accuracy:** 72%
* **Macro Avg:** Precision: 0.45, Recall: 0.29, F1-score: 0.31
* **Weighted Avg:** Precision: 0.65, Recall: 0.72, F1-score: 0.64

## Per-Class Metrics:

| Label                                    |   Precision |   Recall |   F1-score |   Support |
|:-----------------------------------------|------------:|---------:|-----------:|----------:|
| 710: Threatening economic growth         |        0.63 |     0.3  |       0.41 |        63 |
| 720: Threatening national sovereignty    |        1    |     0.15 |       0.26 |        20 |
| 721: Climate conspiracy                  |        0    |     0    |       0    |        15 |
| 722: Scientific scepticism and denial    |        0    |     0    |       0    |        19 |
| 723: Climate movement bashing            |        0.33 |     0.28 |       0.3  |        18 |
| 724: Other polluters as the real problem |        0.77 |     0.8  |       0.78 |        25 |
| 730: Threatening energy security         |        0.6  |     0.09 |       0.16 |        33 |
| 740: Threatening way of life             |        0    |     0    |       0    |        11 |
| 799: None of them                        |        0.73 |     0.99 |       0.84 |       356 |

# Inference platform
This model is used by the [CAP Babel Machine](https://babel.poltextlab.com), an open-source and free natural language processing tool, designed to simplify and speed up projects for comparative research.  

# Cooperation
Model performance can be significantly improved by extending our training sets. We appreciate every submission of CAP-coded corpora (of any domain and language) at poltextlab{at}poltextlab{dot}com or by using the [CAP Babel Machine](https://babel.poltextlab.com).
## Debugging and issues
This architecture uses the `sentencepiece` tokenizer. In order to run the model before `transformers==4.27` you need to install it manually.