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README.md

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+---
+tags:
+- autotrain
+- text-classification
+language:
+- fr
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- huynhdoo/autotrain-data-jva-activity-classification
+co2_eq_emissions:
+  emissions: 12.734050517307358
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 2096367492
+- CO2 Emissions (in grams): 12.7341
+
+## Validation Metrics
+
+- Loss: 0.888
+- Accuracy: 0.812
+- Macro F1: 0.684
+- Micro F1: 0.812
+- Weighted F1: 0.808
+- Macro Precision: 0.708
+- Micro Precision: 0.812
+- Weighted Precision: 0.813
+- Macro Recall: 0.691
+- Micro Recall: 0.812
+- Weighted Recall: 0.812
+
+
+## Usage
+
+You can use cURL to access this model:
+
+```
+$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/huynhdoo/autotrain-jva-activity-classification-2096367492
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("huynhdoo/autotrain-jva-activity-classification-2096367492", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("huynhdoo/autotrain-jva-activity-classification-2096367492", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

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+{
+  "_name_or_path": "AutoTrain",
+  "_num_labels": 38,
+  "architectures": [
+    "CamembertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Accompagnement aux activit\u00e9s sportives",
+    "1": "Accompagnement \u00e0 la mobilit\u00e9",
+    "2": "Accueil / Information",
+    "3": "Actions de sensibilisation",
+    "4": "Aide aux d\u00e9marches administratives",
+    "5": "Alphab\u00e9tisation / Apprentissage du fran\u00e7ais (FLE)",
+    "6": "Am\u00e9nagement d'espaces naturels",
+    "7": "Animation / Loisirs",
+    "8": "Collecte de fonds",
+    "9": "Collecte de produits",
+    "10": "Communication",
+    "11": "Dialogue interculturel",
+    "12": "Distribution",
+    "13": "Droit et conseil juridique",
+    "14": "Gestion administrative",
+    "15": "Gestion de projets",
+    "16": "Gestion des ressources humaines",
+    "17": "Gestion financi\u00e8re / comptabilit\u00e9",
+    "18": "Gouvernance",
+    "19": "Informatique",
+    "20": "Logistique",
+    "21": "Lutte contre l'isolement",
+    "22": "Maraude",
+    "23": "Mentorat & Parrainage",
+    "24": "M\u00e9diation culturelle",
+    "25": "M\u00e9dical",
+    "26": "Ramassage de d\u00e9chets",
+    "27": "Recherche de partenariats",
+    "28": "Secourisme et s\u00e9curit\u00e9 civile",
+    "29": "Services \u00e0 la personne",
+    "30": "Soins aux animaux",
+    "31": "Soutien scolaire et formation",
+    "32": "Traduction",
+    "33": "Travaux manuels",
+    "34": "Valorisation du patrimoine",
+    "35": "Vie citoyenne",
+    "36": "\u00c9coute / Aide psychologique",
+    "37": "\u00c9v\u00e9nementiel"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Accompagnement aux activit\u00e9s sportives": 0,
+    "Accompagnement \u00e0 la mobilit\u00e9": 1,
+    "Accueil / Information": 2,
+    "Actions de sensibilisation": 3,
+    "Aide aux d\u00e9marches administratives": 4,
+    "Alphab\u00e9tisation / Apprentissage du fran\u00e7ais (FLE)": 5,
+    "Am\u00e9nagement d'espaces naturels": 6,
+    "Animation / Loisirs": 7,
+    "Collecte de fonds": 8,
+    "Collecte de produits": 9,
+    "Communication": 10,
+    "Dialogue interculturel": 11,
+    "Distribution": 12,
+    "Droit et conseil juridique": 13,
+    "Gestion administrative": 14,
+    "Gestion de projets": 15,
+    "Gestion des ressources humaines": 16,
+    "Gestion financi\u00e8re / comptabilit\u00e9": 17,
+    "Gouvernance": 18,
+    "Informatique": 19,
+    "Logistique": 20,
+    "Lutte contre l'isolement": 21,
+    "Maraude": 22,
+    "Mentorat & Parrainage": 23,
+    "M\u00e9diation culturelle": 24,
+    "M\u00e9dical": 25,
+    "Ramassage de d\u00e9chets": 26,
+    "Recherche de partenariats": 27,
+    "Secourisme et s\u00e9curit\u00e9 civile": 28,
+    "Services \u00e0 la personne": 29,
+    "Soins aux animaux": 30,
+    "Soutien scolaire et formation": 31,
+    "Traduction": 32,
+    "Travaux manuels": 33,
+    "Valorisation du patrimoine": 34,
+    "Vie citoyenne": 35,
+    "\u00c9coute / Aide psychologique": 36,
+    "\u00c9v\u00e9nementiel": 37
+  },
+  "layer_norm_eps": 1e-05,
+  "max_length": 256,
+  "max_position_embeddings": 514,
+  "model_type": "camembert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "padding": "max_length",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.22.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 32005
+}

pytorch_model.bin

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sentencepiece.bpe.model

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special_tokens_map.json

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

tokenizer_config.json

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+{
+  "additional_special_tokens": [
+    "<s>NOTUSED",
+    "</s>NOTUSED"
+  ],
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": {
+    "__type": "AddedToken",
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "name_or_path": "AutoTrain",
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "sp_model_kwargs": {},
+  "special_tokens_map_file": null,
+  "tokenizer_class": "CamembertTokenizer",
+  "unk_token": "<unk>"
+}