Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,44 @@
|
|
1 |
-
---
|
2 |
-
license: apache-2.0
|
3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
datasets:
|
4 |
+
- gplsi/SocialTOX
|
5 |
+
language:
|
6 |
+
- es
|
7 |
+
metrics:
|
8 |
+
- accuracy
|
9 |
+
- f1
|
10 |
+
- precision
|
11 |
+
- recall
|
12 |
+
base_model:
|
13 |
+
- BSC-LT/roberta-base-bne
|
14 |
+
pipeline_tag: text-classification
|
15 |
+
---
|
16 |
+
|
17 |
+
# 🧠 Toxicity_model_RoBERTa-base-bne– Spanish Toxicity Classifier Binary (Fine-tuned)
|
18 |
+
|
19 |
+
## 📌 Model Description
|
20 |
+
|
21 |
+
This model is a fine-tuned version** of `RoBERTa-base-bne`, specifically trained to classify the toxicity level of **Spanish-language user comments on news articles**. It distinguishes between tow categories:
|
22 |
+
|
23 |
+
- **Non-toxic**
|
24 |
+
- **Toxic**
|
25 |
+
|
26 |
+
The model follows instruction-based prompts and returns a single classification label in response.
|
27 |
+
|
28 |
+
---
|
29 |
+
|
30 |
+
## 📂 Training Data
|
31 |
+
|
32 |
+
The model was fine-tuned on the **[SocialTOX dataset](https://huggingface.co/datasets/gplsi/SocialTOX)**, a collection of Spanish-language comments annotated for varying levels of toxicity. These comments come from news platforms and represent real-world scenarios of online discourse. In this case, a Binary classifier was develop, where the classes \textit{Slightly toxic} and \textit{Toxic} were merged into a single \textit{Toxic} category.
|
33 |
+
|
34 |
+
---
|
35 |
+
|
36 |
+
## Training hyperparameters
|
37 |
+
- epochs: 10
|
38 |
+
- learning_rate: 2.45e-6
|
39 |
+
- beta1: 0.9
|
40 |
+
- beta2: 0.95
|
41 |
+
- Adam_epsilon: 1.00e-8
|
42 |
+
- weight_decay: 0
|
43 |
+
- batch_size: 16
|
44 |
+
- max_seq_length: 512
|