Upload TFBertForSequenceClassification

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_keras_callback
+model-index:
+- name: BERT_Intent_Classifier
+  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. -->
+
+# BERT_Intent_Classifier
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) 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: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 160, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
+- training_precision: float32
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- TensorFlow 2.15.0
+- Datasets 2.16.1
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "CurrentHumanQuery",
+    "1": "SelfAware",
+    "2": "CourtesyGreetingResponse",
+    "3": "Shutup",
+    "4": "GreetingResponse",
+    "5": "NotTalking2U",
+    "6": "GoodBye",
+    "7": "PodBayDoorResponse",
+    "8": "Clever",
+    "9": "NameQuery",
+    "10": "CourtesyGreeting",
+    "11": "Thanks",
+    "12": "Gossip",
+    "13": "UnderstandQuery",
+    "14": "CourtesyGoodBye",
+    "15": "WhoAmI",
+    "16": "Greeting",
+    "17": "Swearing",
+    "18": "RealNameQuery",
+    "19": "TimeQuery",
+    "20": "Jokes",
+    "21": "PodBayDoor"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Clever": 8,
+    "CourtesyGoodBye": 14,
+    "CourtesyGreeting": 10,
+    "CourtesyGreetingResponse": 2,
+    "CurrentHumanQuery": 0,
+    "GoodBye": 6,
+    "Gossip": 12,
+    "Greeting": 16,
+    "GreetingResponse": 4,
+    "Jokes": 20,
+    "NameQuery": 9,
+    "NotTalking2U": 5,
+    "PodBayDoor": 21,
+    "PodBayDoorResponse": 7,
+    "RealNameQuery": 18,
+    "SelfAware": 1,
+    "Shutup": 3,
+    "Swearing": 17,
+    "Thanks": 11,
+    "TimeQuery": 19,
+    "UnderstandQuery": 13,
+    "WhoAmI": 15
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "multi_label_classification",
+  "transformers_version": "4.35.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

tf_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bcbb7791e8be41f7ab61d2b9536b34b8370735ac4aa5cf908f030691cb1bafb9
+size 438284648