Upload TFBertForSequenceClassification
Browse files- README.md +49 -0
- config.json +74 -0
- tf_model.h5 +3 -0
README.md
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---
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license: apache-2.0
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base_model: bert-base-cased
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tags:
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- generated_from_keras_callback
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model-index:
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- name: Symptom_to_Diagnosis
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# Symptom_to_Diagnosis
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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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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- 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': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
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- training_precision: float32
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### Training results
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### Framework versions
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- Transformers 4.35.2
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- TensorFlow 2.15.0
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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config.json
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{
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"_name_or_path": "bert-base-cased",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "allergy",
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"1": "arthritis",
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"2": "bronchial asthma",
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"3": "cervical spondylosis",
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"4": "chicken pox",
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"5": "common cold",
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"6": "dengue",
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"7": "diabetes",
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"8": "drug reaction",
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"9": "fungal infection",
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"10": "gastroesophageal reflux disease",
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"11": "hypertension",
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"12": "impetigo",
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"13": "jaundice",
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"14": "malaria",
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"15": "migraine",
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"16": "peptic ulcer disease",
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"17": "pneumonia",
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"18": "psoriasis",
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"19": "typhoid",
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"20": "urinary tract infection",
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"21": "varicose veins"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"allergy": 0,
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"arthritis": 1,
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"bronchial asthma": 2,
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"cervical spondylosis": 3,
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"chicken pox": 4,
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"common cold": 5,
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"dengue": 6,
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"diabetes": 7,
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"drug reaction": 8,
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"fungal infection": 9,
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"gastroesophageal reflux disease": 10,
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"hypertension": 11,
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"impetigo": 12,
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"jaundice": 13,
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"malaria": 14,
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"migraine": 15,
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"peptic ulcer disease": 16,
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"pneumonia": 17,
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"psoriasis": 18,
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"typhoid": 19,
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"urinary tract infection": 20,
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"varicose veins": 21
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_attentions": true,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"transformers_version": "4.35.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 28996
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}
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:73315602de57db10b2ee1adcaec8d386d4134aaafcdf1a9ac1a8994723037a46
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size 433596776
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