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media2-25-26-v1-1001

This model uses the poltextLAB Media2 codebook built on top of the CAP codebook.

How to use the model

from transformers import AutoTokenizer, pipeline

tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-large")
pipe = pipeline(
    model="poltextlab/media2-25-26-v1-1001",
    task="text-classification",
    tokenizer=tokenizer,
    use_fast=False,
    token="<your_hf_read_only_token>"
)

text = "<text_to_classify>"
pipe(text)

Classification Report

Overall Performance:

Evaluated on a test set of 1601 English samples.

Accuracy: 71%
Macro Avg: Precision: 0.67, Recall: 0.62, F1-score: 0.62
Weighted Avg: Precision: 0.74, Recall: 0.71, F1-score: 0.70

Per-Class Metrics:

Label	Precision	Recall	F1-score	Support
1	0.77	0.8	0.78	50
2	0.74	0.78	0.76	50
3	0.74	0.74	0.74	50
4	0.7	0.86	0.77	50
5	0.86	0.76	0.81	50
6	0.83	0.98	0.9	50
7	0.85	0.88	0.86	50
8	0.87	0.94	0.9	50
9	0.87	0.82	0.85	50
10	0.77	0.94	0.85	50
12	0.56	0.88	0.69	50
13	0.88	0.86	0.87	50
14	0.73	0.76	0.75	50
15	0.51	0.86	0.64	50
16	0.75	0.86	0.8	50
17	0.63	0.76	0.69	50
18	0.91	0.82	0.86	50
19	0.51	0.82	0.63	50
20	0.62	0.92	0.74	50
21	0.75	0.8	0.78	50
23	0.52	0.78	0.62	50
24	0.71	0.57	0.63	42
25	0.92	0.48	0.63	23
26	0.92	0.56	0.7	43
27	0	0	0	18
28	0	0	0	9
29	0.43	0.27	0.33	33
30	0.72	0.28	0.41	46
31	0.89	0.44	0.59	36
32	0	0	0	20
33	0.12	0.08	0.1	12
34	0.07	0.14	0.1	7
35	0.93	0.71	0.81	35
36	0	0	0	3
37	1	0.82	0.9	44
38	0.81	0.81	0.81	42
39	1	0.39	0.57	33
40	0.88	0.21	0.34	33
41	1	0.78	0.88	32
998	0.92	0.55	0.69	40

Inference platform

This model is used by the CAP Babel Machine, 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.

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.

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CAP Media/Media2 Babel

Collection

Models for CAP classification with additional media codes. • 10 items • Updated 19 days ago

Evaluation results

Accuracy
self-reported

71%
F1-Score
self-reported

70%

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