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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|
| 1 |
+
{
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| 2 |
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"_name_or_path": "flaubert/flaubert_base_cased",
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| 3 |
+
"amp": 1,
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| 4 |
+
"architectures": [
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"FlaubertForSequenceClassification"
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+
],
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"asm": false,
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| 8 |
+
"attention_dropout": 0.1,
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| 9 |
+
"bos_index": 0,
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| 10 |
+
"bos_token_id": 0,
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| 11 |
+
"bptt": 512,
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+
"causal": false,
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| 13 |
+
"clip_grad_norm": 5,
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| 14 |
+
"dropout": 0.1,
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| 15 |
+
"emb_dim": 768,
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| 16 |
+
"embed_init_std": 0.02209708691207961,
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| 17 |
+
"encoder_only": true,
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| 18 |
+
"end_n_top": 5,
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| 19 |
+
"eos_index": 1,
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| 20 |
+
"fp16": true,
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| 21 |
+
"gelu_activation": true,
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| 22 |
+
"group_by_size": true,
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| 23 |
+
"id2label": {
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| 24 |
+
"0": "Taxes",
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| 25 |
+
"1": "Esth\u00e9tique",
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| 26 |
+
"2": "Ch\u00e8ques",
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| 27 |
+
"3": "Baby-sitters & Cr\u00e8ches",
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| 28 |
+
"4": "Entretien",
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| 29 |
+
"5": "Frais juridique",
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| 30 |
+
"6": "Internet",
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| 31 |
+
"7": "Billets de train",
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+
"8": "Sport",
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| 33 |
+
"9": "H\u00f4tels",
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| 34 |
+
"10": "Transports en commun",
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| 35 |
+
"11": "Assurance habitation",
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| 36 |
+
"12": "TVA",
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| 37 |
+
"13": "Alimentation - Autres",
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| 38 |
+
"14": "Carburant",
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| 39 |
+
"15": "Frais bancaires",
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| 40 |
+
"16": "D\u00e9p\u00f4t d'argent",
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| 41 |
+
"17": "D\u00e9bit mensuel carte",
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| 42 |
+
"18": "Sant\u00e9 - Autres",
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| 43 |
+
"19": "Publicit\u00e9",
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| 44 |
+
"20": "Stationnement",
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| 45 |
+
"21": "Pr\u00e9voyance",
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| 46 |
+
"22": "Spa & Massage",
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| 47 |
+
"23": "Extra",
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| 48 |
+
"24": "T\u00e9l\u00e9phonie mobile",
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| 49 |
+
"25": "Articles de sport",
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| 50 |
+
"26": "Musique",
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| 51 |
+
"27": "Loyer",
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| 52 |
+
"28": "Salaires",
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| 53 |
+
"29": "Livres",
|
| 54 |
+
"30": "C\u00e2ble / Satellite",
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| 55 |
+
"31": "Divertissements",
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| 56 |
+
"32": "Billets d'avion",
|
| 57 |
+
"33": "Virements internes",
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| 58 |
+
"34": "Entretien v\u00e9hicule",
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| 59 |
+
"35": "P\u00e9age",
|
| 60 |
+
"36": "Remboursements",
|
| 61 |
+
"37": "Hypoth\u00e8que",
|
| 62 |
+
"38": "Cadeaux",
|
| 63 |
+
"39": "Conseils",
|
| 64 |
+
"40": "V\u00eatements/Chaussures",
|
| 65 |
+
"41": "Remboursement emprunt",
|
| 66 |
+
"42": "Auto & Transports - Autres",
|
| 67 |
+
"43": "Marketing",
|
| 68 |
+
"44": "Esth\u00e9tique & Soins - Autres",
|
| 69 |
+
"45": "Sortie au restaurant",
|
| 70 |
+
"46": "Subventions",
|
| 71 |
+
"47": "Pressing",
|
| 72 |
+
"48": "Sports d'hiver",
|
| 73 |
+
"49": "R\u00e9mun\u00e9rations dirigeants",
|
| 74 |
+
"50": "Cosm\u00e9tique",
|
| 75 |
+
"51": "Charges diverses",
|
| 76 |
+
"52": "Retraite",
|
| 77 |
+
"53": "Autres rentr\u00e9es",
|
| 78 |
+
"54": "Allocations et pensions",
|
| 79 |
+
"55": "Dons",
|
| 80 |
+
"56": "Economies",
|
| 81 |
+
"57": "Comptabilit\u00e9",
|
| 82 |
+
"58": "Frais d'impressions",
|
| 83 |
+
"59": "Jouets",
|
| 84 |
+
"60": "Taxe d'apprentissage",
|
| 85 |
+
"61": "Imp\u00f4ts & Taxes - Autres",
|
| 86 |
+
"62": "Fast foods",
|
| 87 |
+
"63": "Tabac",
|
| 88 |
+
"64": "Licences",
|
| 89 |
+
"65": "Supermarch\u00e9 / Epicerie",
|
| 90 |
+
"66": "M\u00e9decin",
|
| 91 |
+
"67": "Frais d'exp\u00e9ditions",
|
| 92 |
+
"68": "Ecole",
|
| 93 |
+
"69": "Films & DVDs",
|
| 94 |
+
"70": "Emprunt",
|
| 95 |
+
"71": "Pharmacie",
|
| 96 |
+
"72": "Incidents de paiement",
|
| 97 |
+
"73": "Autres d\u00e9penses",
|
| 98 |
+
"74": "Sorties culturelles",
|
| 99 |
+
"75": "Voyages / Vacances",
|
| 100 |
+
"76": "Logement \u00e9tudiant",
|
| 101 |
+
"77": "Frais Animaux",
|
| 102 |
+
"78": "Mutuelle",
|
| 103 |
+
"79": "Electricit\u00e9",
|
| 104 |
+
"80": "Ext\u00e9rieur et jardin",
|
| 105 |
+
"81": "Assurance",
|
| 106 |
+
"82": "Opticien / Ophtalmo.",
|
| 107 |
+
"83": "D\u00e9penses pro - Autres",
|
| 108 |
+
"84": "Amendes",
|
| 109 |
+
"85": "Epargne",
|
| 110 |
+
"86": "Abonnements - Autres",
|
| 111 |
+
"87": "Bars / Clubs",
|
| 112 |
+
"88": "Dentiste",
|
| 113 |
+
"89": "Retraits",
|
| 114 |
+
"90": "Fournitures de bureau",
|
| 115 |
+
"91": "Loisirs & Sorties - Autres",
|
| 116 |
+
"92": "Coiffeur",
|
| 117 |
+
"93": "Banque - Autres",
|
| 118 |
+
"94": "Eau",
|
| 119 |
+
"95": "Sous-traitance",
|
| 120 |
+
"96": "D\u00e9coration",
|
| 121 |
+
"97": "Logement - Autres",
|
| 122 |
+
"98": "Gaz",
|
| 123 |
+
"99": "Location de v\u00e9hicule",
|
| 124 |
+
"100": "Imp\u00f4ts fonciers",
|
| 125 |
+
"101": "Services Bancaires",
|
| 126 |
+
"102": "Hobbies",
|
| 127 |
+
"103": "Virements",
|
| 128 |
+
"104": "Ventes",
|
| 129 |
+
"105": "Loyers re\u00e7us",
|
| 130 |
+
"106": "A cat\u00e9goriser",
|
| 131 |
+
"107": "Services",
|
| 132 |
+
"108": "Services en ligne",
|
| 133 |
+
"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 |
+
"115": "Assurance v\u00e9hicule",
|
| 140 |
+
"116": "Restaurants",
|
| 141 |
+
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|
| 38 |
+
"normalized": false,
|
| 39 |
+
"rstrip": false,
|
| 40 |
+
"single_word": false,
|
| 41 |
+
"special": true
|
| 42 |
+
},
|
| 43 |
+
"5": {
|
| 44 |
+
"content": "<special1>",
|
| 45 |
+
"lstrip": false,
|
| 46 |
+
"normalized": false,
|
| 47 |
+
"rstrip": false,
|
| 48 |
+
"single_word": false,
|
| 49 |
+
"special": true
|
| 50 |
+
},
|
| 51 |
+
"6": {
|
| 52 |
+
"content": "<special2>",
|
| 53 |
+
"lstrip": false,
|
| 54 |
+
"normalized": false,
|
| 55 |
+
"rstrip": false,
|
| 56 |
+
"single_word": false,
|
| 57 |
+
"special": true
|
| 58 |
+
},
|
| 59 |
+
"7": {
|
| 60 |
+
"content": "<special3>",
|
| 61 |
+
"lstrip": false,
|
| 62 |
+
"normalized": false,
|
| 63 |
+
"rstrip": false,
|
| 64 |
+
"single_word": false,
|
| 65 |
+
"special": true
|
| 66 |
+
},
|
| 67 |
+
"8": {
|
| 68 |
+
"content": "<special4>",
|
| 69 |
+
"lstrip": false,
|
| 70 |
+
"normalized": false,
|
| 71 |
+
"rstrip": false,
|
| 72 |
+
"single_word": false,
|
| 73 |
+
"special": true
|
| 74 |
+
},
|
| 75 |
+
"9": {
|
| 76 |
+
"content": "<special5>",
|
| 77 |
+
"lstrip": false,
|
| 78 |
+
"normalized": false,
|
| 79 |
+
"rstrip": false,
|
| 80 |
+
"single_word": false,
|
| 81 |
+
"special": true
|
| 82 |
+
},
|
| 83 |
+
"10": {
|
| 84 |
+
"content": "<special6>",
|
| 85 |
+
"lstrip": false,
|
| 86 |
+
"normalized": false,
|
| 87 |
+
"rstrip": false,
|
| 88 |
+
"single_word": false,
|
| 89 |
+
"special": true
|
| 90 |
+
},
|
| 91 |
+
"11": {
|
| 92 |
+
"content": "<special7>",
|
| 93 |
+
"lstrip": false,
|
| 94 |
+
"normalized": false,
|
| 95 |
+
"rstrip": false,
|
| 96 |
+
"single_word": false,
|
| 97 |
+
"special": true
|
| 98 |
+
},
|
| 99 |
+
"12": {
|
| 100 |
+
"content": "<special8>",
|
| 101 |
+
"lstrip": false,
|
| 102 |
+
"normalized": false,
|
| 103 |
+
"rstrip": false,
|
| 104 |
+
"single_word": false,
|
| 105 |
+
"special": true
|
| 106 |
+
},
|
| 107 |
+
"13": {
|
| 108 |
+
"content": "<special9>",
|
| 109 |
+
"lstrip": false,
|
| 110 |
+
"normalized": false,
|
| 111 |
+
"rstrip": false,
|
| 112 |
+
"single_word": false,
|
| 113 |
+
"special": true
|
| 114 |
+
}
|
| 115 |
+
},
|
| 116 |
+
"additional_special_tokens": [
|
| 117 |
+
"<special0>",
|
| 118 |
+
"<special1>",
|
| 119 |
+
"<special2>",
|
| 120 |
+
"<special3>",
|
| 121 |
+
"<special4>",
|
| 122 |
+
"<special5>",
|
| 123 |
+
"<special6>",
|
| 124 |
+
"<special7>",
|
| 125 |
+
"<special8>",
|
| 126 |
+
"<special9>"
|
| 127 |
+
],
|
| 128 |
+
"bos_token": "<s>",
|
| 129 |
+
"clean_up_tokenization_spaces": true,
|
| 130 |
+
"cls_token": "</s>",
|
| 131 |
+
"do_lower_case": false,
|
| 132 |
+
"id2lang": null,
|
| 133 |
+
"lang2id": null,
|
| 134 |
+
"mask_token": "<special1>",
|
| 135 |
+
"model_max_length": 512,
|
| 136 |
+
"pad_token": "<pad>",
|
| 137 |
+
"sep_token": "</s>",
|
| 138 |
+
"tokenizer_class": "FlaubertTokenizer",
|
| 139 |
+
"unk_token": "<unk>"
|
| 140 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f61f85c5a97b6db5a59ff5a06f3b7b4d9ac62ce87b819291d65fbf7027758e4b
|
| 3 |
+
size 5112
|
vocab.json
ADDED
|
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|
|
|