End of training
Browse files- README.md +52 -0
- config.json +325 -0
- logs/events.out.tfevents.1718202403.pytorch-2-0-0-gpu-p-ml-g5-12xlarge-bd6adb7f7a95188f931aa4f47fd4 +3 -0
- logs/events.out.tfevents.1718203072.pytorch-2-0-0-gpu-p-ml-g5-12xlarge-bd6adb7f7a95188f931aa4f47fd4 +3 -0
- logs/events.out.tfevents.1718203388.pytorch-2-0-0-gpu-p-ml-g5-12xlarge-bd6adb7f7a95188f931aa4f47fd4 +3 -0
- logs/events.out.tfevents.1718203821.pytorch-2-0-0-gpu-p-ml-g5-12xlarge-bd6adb7f7a95188f931aa4f47fd4 +3 -0
- logs/events.out.tfevents.1718204662.pytorch-2-0-0-gpu-p-ml-g5-12xlarge-bd6adb7f7a95188f931aa4f47fd4 +3 -0
- logs/events.out.tfevents.1718206952.pytorch-2-0-0-gpu-p-ml-g5-12xlarge-bd6adb7f7a95188f931aa4f47fd4 +3 -0
- merges.txt +0 -0
- model.safetensors +3 -0
- special_tokens_map.json +20 -0
- tokenizer_config.json +140 -0
- training_args.bin +3 -0
- vocab.json +0 -0
README.md
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---
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license: mit
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base_model: flaubert/flaubert_base_cased
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tags:
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- generated_from_trainer
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model-index:
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- name: bert-base-banking77-pt2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bert-base-banking77-pt2
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This model is a fine-tuned version of [flaubert/flaubert_base_cased](https://huggingface.co/flaubert/flaubert_base_cased) on the None dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 1024
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 1
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### Training results
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.1+cu121
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "flaubert/flaubert_base_cased",
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"amp": 1,
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"architectures": [
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"FlaubertForSequenceClassification"
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],
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"asm": false,
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"attention_dropout": 0.1,
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"bos_index": 0,
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"bos_token_id": 0,
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"bptt": 512,
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"causal": false,
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"clip_grad_norm": 5,
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"dropout": 0.1,
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"emb_dim": 768,
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"embed_init_std": 0.02209708691207961,
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"encoder_only": true,
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"end_n_top": 5,
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"eos_index": 1,
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"fp16": true,
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"gelu_activation": true,
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"group_by_size": true,
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"id2label": {
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"0": "Taxes",
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"1": "Esth\u00e9tique",
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"2": "Ch\u00e8ques",
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"3": "Baby-sitters & Cr\u00e8ches",
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"4": "Entretien",
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"5": "Frais juridique",
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"6": "Internet",
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"7": "Billets de train",
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"8": "Sport",
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"9": "H\u00f4tels",
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"10": "Transports en commun",
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"11": "Assurance habitation",
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"12": "TVA",
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"13": "Alimentation - Autres",
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"14": "Carburant",
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"15": "Frais bancaires",
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"16": "D\u00e9p\u00f4t d'argent",
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"17": "D\u00e9bit mensuel carte",
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"18": "Sant\u00e9 - Autres",
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"19": "Publicit\u00e9",
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"20": "Stationnement",
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"21": "Pr\u00e9voyance",
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"22": "Spa & Massage",
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"23": "Extra",
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"24": "T\u00e9l\u00e9phonie mobile",
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"25": "Articles de sport",
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"26": "Musique",
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"27": "Loyer",
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"28": "Salaires",
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"29": "Livres",
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"30": "C\u00e2ble / Satellite",
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"31": "Divertissements",
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"32": "Billets d'avion",
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"33": "Virements internes",
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"34": "Entretien v\u00e9hicule",
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"35": "P\u00e9age",
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"36": "Remboursements",
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"37": "Hypoth\u00e8que",
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"38": "Cadeaux",
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"39": "Conseils",
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"40": "V\u00eatements/Chaussures",
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"41": "Remboursement emprunt",
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"42": "Auto & Transports - Autres",
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"43": "Marketing",
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"44": "Esth\u00e9tique & Soins - Autres",
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"45": "Sortie au restaurant",
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"46": "Subventions",
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"47": "Pressing",
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"48": "Sports d'hiver",
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"49": "R\u00e9mun\u00e9rations dirigeants",
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"50": "Cosm\u00e9tique",
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"51": "Charges diverses",
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"52": "Retraite",
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"53": "Autres rentr\u00e9es",
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"54": "Allocations et pensions",
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"55": "Dons",
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"56": "Economies",
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"57": "Comptabilit\u00e9",
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"58": "Frais d'impressions",
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"59": "Jouets",
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"60": "Taxe d'apprentissage",
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"61": "Imp\u00f4ts & Taxes - Autres",
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"62": "Fast foods",
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"63": "Tabac",
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"64": "Licences",
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"65": "Supermarch\u00e9 / Epicerie",
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"66": "M\u00e9decin",
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"67": "Frais d'exp\u00e9ditions",
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"68": "Ecole",
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"69": "Films & DVDs",
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"70": "Emprunt",
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"71": "Pharmacie",
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"72": "Incidents de paiement",
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"73": "Autres d\u00e9penses",
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"74": "Sorties culturelles",
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"75": "Voyages / Vacances",
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"76": "Logement \u00e9tudiant",
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"77": "Frais Animaux",
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+
"78": "Mutuelle",
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+
"79": "Electricit\u00e9",
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"80": "Ext\u00e9rieur et jardin",
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+
"81": "Assurance",
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"82": "Opticien / Ophtalmo.",
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+
"83": "D\u00e9penses pro - Autres",
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+
"84": "Amendes",
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+
"85": "Epargne",
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+
"86": "Abonnements - Autres",
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+
"87": "Bars / Clubs",
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"88": "Dentiste",
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+
"89": "Retraits",
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+
"90": "Fournitures de bureau",
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+
"91": "Loisirs & Sorties - Autres",
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116 |
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"92": "Coiffeur",
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117 |
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"93": "Banque - Autres",
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118 |
+
"94": "Eau",
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+
"95": "Sous-traitance",
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120 |
+
"96": "D\u00e9coration",
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121 |
+
"97": "Logement - Autres",
|
122 |
+
"98": "Gaz",
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123 |
+
"99": "Location de v\u00e9hicule",
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124 |
+
"100": "Imp\u00f4ts fonciers",
|
125 |
+
"101": "Services Bancaires",
|
126 |
+
"102": "Hobbies",
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127 |
+
"103": "Virements",
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128 |
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"104": "Ventes",
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129 |
+
"105": "Loyers re\u00e7us",
|
130 |
+
"106": "A cat\u00e9goriser",
|
131 |
+
"107": "Services",
|
132 |
+
"108": "Services en ligne",
|
133 |
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"109": "Maintenance bureaux",
|
134 |
+
"110": "Notes de frais",
|
135 |
+
"111": "Achats & Shopping - Autres",
|
136 |
+
"112": "Pensions",
|
137 |
+
"113": "Fournitures scolaires",
|
138 |
+
"114": "High Tech",
|
139 |
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"115": "Assurance v\u00e9hicule",
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140 |
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"116": "Restaurants",
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141 |
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"117": "Int\u00e9r\u00eats",
|
142 |
+
"118": "Scolarit\u00e9 & Enfants - Autres",
|
143 |
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"119": "Caf\u00e9"
|
144 |
+
},
|
145 |
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"id2lang": {
|
146 |
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"0": "fr"
|
147 |
+
},
|
148 |
+
"init_std": 0.02,
|
149 |
+
"is_encoder": true,
|
150 |
+
"label2id": {
|
151 |
+
"A cat\u00e9goriser": 106,
|
152 |
+
"Abonnements - Autres": 86,
|
153 |
+
"Achats & Shopping - Autres": 111,
|
154 |
+
"Alimentation - Autres": 13,
|
155 |
+
"Allocations et pensions": 54,
|
156 |
+
"Amendes": 84,
|
157 |
+
"Articles de sport": 25,
|
158 |
+
"Assurance": 81,
|
159 |
+
"Assurance habitation": 11,
|
160 |
+
"Assurance v\u00e9hicule": 115,
|
161 |
+
"Auto & Transports - Autres": 42,
|
162 |
+
"Autres d\u00e9penses": 73,
|
163 |
+
"Autres rentr\u00e9es": 53,
|
164 |
+
"Baby-sitters & Cr\u00e8ches": 3,
|
165 |
+
"Banque - Autres": 93,
|
166 |
+
"Bars / Clubs": 87,
|
167 |
+
"Billets d'avion": 32,
|
168 |
+
"Billets de train": 7,
|
169 |
+
"Cadeaux": 38,
|
170 |
+
"Caf\u00e9": 119,
|
171 |
+
"Carburant": 14,
|
172 |
+
"Charges diverses": 51,
|
173 |
+
"Ch\u00e8ques": 2,
|
174 |
+
"Coiffeur": 92,
|
175 |
+
"Comptabilit\u00e9": 57,
|
176 |
+
"Conseils": 39,
|
177 |
+
"Cosm\u00e9tique": 50,
|
178 |
+
"C\u00e2ble / Satellite": 30,
|
179 |
+
"Dentiste": 88,
|
180 |
+
"Divertissements": 31,
|
181 |
+
"Dons": 55,
|
182 |
+
"D\u00e9bit mensuel carte": 17,
|
183 |
+
"D\u00e9coration": 96,
|
184 |
+
"D\u00e9penses pro - Autres": 83,
|
185 |
+
"D\u00e9p\u00f4t d'argent": 16,
|
186 |
+
"Eau": 94,
|
187 |
+
"Ecole": 68,
|
188 |
+
"Economies": 56,
|
189 |
+
"Electricit\u00e9": 79,
|
190 |
+
"Emprunt": 70,
|
191 |
+
"Entretien": 4,
|
192 |
+
"Entretien v\u00e9hicule": 34,
|
193 |
+
"Epargne": 85,
|
194 |
+
"Esth\u00e9tique": 1,
|
195 |
+
"Esth\u00e9tique & Soins - Autres": 44,
|
196 |
+
"Extra": 23,
|
197 |
+
"Ext\u00e9rieur et jardin": 80,
|
198 |
+
"Fast foods": 62,
|
199 |
+
"Films & DVDs": 69,
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200 |
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"Fournitures de bureau": 90,
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201 |
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"Fournitures scolaires": 113,
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