Upload TFXLMRobertaForSequenceClassification

README.md

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+---
+library_name: transformers
+tags:
+- generated_from_keras_callback
+model-index:
+- name: FR-categories_multilingual-e5-base
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+
+# FR-categories_multilingual-e5-base
+
+This model was trained from scratch on an unknown dataset.
+It achieves the following results on the evaluation set:
+
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- optimizer: None
+- training_precision: float32
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- TensorFlow 2.18.0
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+{
+  "_name_or_path": "/home/dev/Python/AI/Semantix/Classification/FR-categories_multilingual-e5-base",
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "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": "crime, droit et justice",
+    "1": "arts, culture, divertissement et m\u00e9dias",
+    "2": "\u00e9conomie, affaires et finance",
+    "3": "catastrophe, accident et incident d'urgence",
+    "4": "environnement",
+    "5": "\u00e9ducation",
+    "6": "sant\u00e9",
+    "7": "int\u00e9r\u00eat humain",
+    "8": "style de vie et loisirs",
+    "9": "politique",
+    "10": "travail",
+    "11": "religion et croyance",
+    "12": "science et technologie",
+    "13": "soci\u00e9t\u00e9",
+    "14": "sport",
+    "15": "conflit, guerre et paix",
+    "16": "m\u00e9t\u00e9o"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "arts, culture, divertissement et m\u00e9dias": 1,
+    "catastrophe, accident et incident d'urgence": 3,
+    "conflit, guerre et paix": 15,
+    "crime, droit et justice": 0,
+    "environnement": 4,
+    "int\u00e9r\u00eat humain": 7,
+    "m\u00e9t\u00e9o": 16,
+    "politique": 9,
+    "religion et croyance": 11,
+    "sant\u00e9": 6,
+    "science et technologie": 12,
+    "soci\u00e9t\u00e9": 13,
+    "sport": 14,
+    "style de vie et loisirs": 8,
+    "travail": 10,
+    "\u00e9conomie, affaires et finance": 2,
+    "\u00e9ducation": 5
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

tf_model.h5

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+oid sha256:f96fcd4d9cb384d21f57b123e38e9beb642386d9a47f4aac606dd64d175b866d
+size 1112516416