Add multi-label RoBERTuito+CL2 (hate + target-group detection) + model card

README.md

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+---
+language: es
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-classification
+base_model: pysentimiento/robertuito-base-uncased
+tags:
+  - hate-speech-detection
+  - multi-label
+  - target-group-detection
+  - chilean-spanish
+  - spanish
+  - social-media
+  - roberta
+datasets:
+  - CL2
+metrics:
+  - f1
+  - roc_auc
+widget:
+  - text: "estos inmigrantes de mierda que se vayan de mi pais"
+  - text: "las minas no saben manejar, mejor que se queden en la casa"
+---
+
+# RoBERTuito + CL2 — multi-label hate speech and target-group detection (Chilean Spanish)
+
+A **multi-label** classifier for Chilean Spanish social-media text. For each
+message it predicts, independently, **five** binary targets:
+
+| Target | Meaning |
+|---|---|
+| `hate` | the message is hate speech |
+| `women` | it references women |
+| `lgbtq` | it references the LGBTQ+ community |
+| `immigrants` | it references immigrant communities |
+| `indigenous` | it references Indigenous (Native American) peoples |
+
+So it detects both **whether** a message is hateful **and which protected
+group(s) it targets or mentions**. It is [RoBERTuito](https://huggingface.co/pysentimiento/robertuito-base-uncased)
+fine-tuned on the **CL2** corpus, using both its hate/non-hate label and its
+target-group annotations.
+
+This is a companion to
+[`mmendoza/robertuito-cl2-hate-speech`](https://huggingface.co/mmendoza/robertuito-cl2-hate-speech)
+(binary hate/non-hate). Use the binary model if you only need hate detection;
+use this one if you also need the targeted group. The group layer is a secondary
+annotation in CL2 and is not part of the main results in the paper.
+
+## Usage
+
+The model **requires the same normalisation used at training** (mentions →
+`@usuario`, links → `url`, lowercase). Outputs are **independent sigmoids**
+(multi-label), not a softmax.
+
+```python
+import re, torch
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+_user = re.compile(r"@\w+"); _url = re.compile(r"https?://\S+|www\.\S+")
+def preprocess(t):
+    return _url.sub("url", _user.sub("@usuario", str(t))).lower().strip()
+
+name = "mmendoza/robertuito-cl2-multigroup"
+tok = AutoTokenizer.from_pretrained(name)
+model = AutoModelForSequenceClassification.from_pretrained(name).eval()
+labels = [model.config.id2label[i] for i in range(model.config.num_labels)]
+
+text = "estos inmigrantes de mierda que se vayan de mi pais"
+enc = tok(preprocess(text), return_tensors="pt", truncation=True, max_length=128)
+with torch.no_grad():
+    probs = torch.sigmoid(model(**enc).logits)[0]
+for lab, p in zip(labels, probs):
+    flag = "  <-- active" if p >= 0.5 else ""
+    print(f"{lab:11s} {p:.3f}{flag}")
+```
+
+Label order: `hate, women, lgbtq, immigrants, indigenous`. Each is an independent
+probability; threshold at 0.5 (tune per target if needed).
+
+## Training data
+
+**CL2** — 4,547 Chilean Spanish tweets, 45.6 % hate, annotated by three
+independent annotators (majority vote) for a hate/non-hate label and for four
+target groups. Group prevalence (majority vote): women 17.2 %, immigrants
+14.5 %, Indigenous 12.8 %, LGBTQ+ 10.8 %. A tweet can reference more than one
+group. Corpus: https://zenodo.org/records/14619078
+
+## Training procedure
+
+Fine-tuned with a multi-label head (`problem_type="multi_label_classification"`,
+`BCEWithLogitsLoss`) on the full CL2 corpus:
+
+| Hyperparameter | Value |
+|---|---|
+| Base model | `pysentimiento/robertuito-base-uncased` |
+| Epochs | 5 |
+| Batch size | 32 |
+| Learning rate | 5e-5 |
+| Max sequence length | 128 |
+| Weight decay | 0.01 |
+| Warmup ratio | 0.1 |
+| Precision | fp16 |
+| Seed | 42 |
+
+## Evaluation
+
+Held-out 20 % of CL2 (stratified on the hate label, n = 910), threshold 0.5:
+
+| Target | Precision | Recall | F1 | AUC |
+|---|---|---|---|---|
+| hate | 0.846 | 0.884 | 0.865 | 0.935 |
+| women | 0.741 | 0.818 | 0.778 | 0.960 |
+| lgbtq | 0.739 | 0.791 | 0.764 | 0.970 |
+| immigrants | 0.878 | 0.915 | 0.896 | 0.994 |
+| indigenous | 0.946 | 0.911 | 0.928 | 0.991 |
+| **macro-F1** | | | **0.846** | |
+| **micro-F1** | | | **0.853** | |
+
+Group detection is even stronger than hate detection (group references are more
+lexical/topical), and adding the group targets does not degrade the hate output
+(F1 0.865 vs 0.854 for the binary-only model).
+
+*(The released weights are trained on the full CL2 corpus for deployment; the
+figures above come from a held-out split.)*
+
+## Limitations and biases
+
+- **Scope is Chilean Spanish** and the **four groups annotated in CL2** (women,
+  immigrants, Indigenous peoples, LGBTQ+). Other targets and varieties are out
+  of scope.
+- The group layer is a **secondary annotation**; per-group performance depends
+  on each group's prevalence and is lower for rarer groups.
+- Trained on keyword/hashtag/account-sampled data, which over-represents explicit
+  hate; the model can err on colloquial profanity and on non-hateful mentions of
+  a group. Use human review for consequential decisions.
+- The model detects the group **referenced** in a message, which is not always
+  the group being **attacked**; read the `hate` and group outputs together.
+
+## Citation
+
+```bibtex
+@article{benoit_hate_chilean_spanish,
+  title   = {Hate speech detection in Chilean Spanish and its cross-lingual transferability},
+  author  = {Benoit, Domingo and {\~N}anculef, Ricardo and Mendoza, Marcelo},
+  journal = {International Journal of Data Science and Analytics (under review)},
+  year    = {2026}
+}
+```
+
+Please also cite the base model (Pérez et al., RoBERTuito, LREC 2022) and the CL2
+corpus (Zenodo 14619078).

config.json

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+{
+  "_name_or_path": "pysentimiento/robertuito-base-uncased",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "hate",
+    "1": "women",
+    "2": "lgbtq",
+    "3": "immigrants",
+    "4": "indigenous"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "hate": 0,
+    "immigrants": 3,
+    "indigenous": 4,
+    "lgbtq": 2,
+    "women": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 130,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "multi_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 30000
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1ffd69d0903425f7ff68f482c96d359bf85ae2835a07096f9b47f8832bdffd3f
+size 435188308

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "4": {
+      "content": "<mask>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 128,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_to_multiple_of": null,
+  "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "</s>",
+  "stride": 0,
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<unk>"
+}