Text Classification
Transformers
Safetensors
Kabyle
ber
xlm-roberta
emotion-classification
african-languages
amazigh
low-resource
goemotions
afro-asiatic
Eval Results (legacy)
text-embeddings-inference
Instructions to use boffire/kabyle-emotion-afro-xlmr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boffire/kabyle-emotion-afro-xlmr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boffire/kabyle-emotion-afro-xlmr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boffire/kabyle-emotion-afro-xlmr") model = AutoModelForSequenceClassification.from_pretrained("boffire/kabyle-emotion-afro-xlmr") - Notebooks
- Google Colab
- Kaggle
v3: epoch 5, 28 GoEmotions classes, AfroXLMR-Large, 0.817 val F1
Browse files- config.json +91 -0
- model.safetensors +3 -0
config.json
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{
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"add_cross_attention": false,
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"architectures": [
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"XLMRobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"dtype": "float32",
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "admiration",
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"1": "amusement",
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"2": "anger",
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"3": "annoyance",
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"4": "approval",
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"5": "caring",
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"6": "confusion",
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"7": "curiosity",
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"8": "desire",
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"9": "disappointment",
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"10": "disapproval",
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"11": "disgust",
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"12": "embarrassment",
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"13": "excitement",
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"14": "fear",
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"15": "gratitude",
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"16": "grief",
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"17": "joy",
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"18": "love",
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"19": "nervousness",
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"20": "neutral",
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"21": "optimism",
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"22": "pride",
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"23": "realization",
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"24": "relief",
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"25": "remorse",
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"26": "sadness",
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"27": "surprise"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"is_decoder": false,
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"label2id": {
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"admiration": 0,
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"amusement": 1,
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"anger": 2,
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"annoyance": 3,
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"approval": 4,
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"caring": 5,
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"confusion": 6,
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"curiosity": 7,
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"desire": 8,
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"disappointment": 9,
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"disapproval": 10,
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"disgust": 11,
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"embarrassment": 12,
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"excitement": 13,
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"fear": 14,
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"gratitude": 15,
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"grief": 16,
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"joy": 17,
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"love": 18,
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"nervousness": 19,
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"neutral": 20,
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"optimism": 21,
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"pride": 22,
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"realization": 23,
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"relief": 24,
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"remorse": 25,
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"sadness": 26,
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"surprise": 27
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "xlm-roberta",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"output_past": true,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"tie_word_embeddings": true,
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"transformers_version": "5.0.0",
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"type_vocab_size": 1,
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"use_cache": false,
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"vocab_size": 250002
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:29dbf2dde257adbe35bc1ed4aa9d3ba6c1252b684a926ce4ee358706fba4b157
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size 2239725224
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