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  1. README.md +58 -0
  2. config.json +50 -0
  3. special_tokens_map.json +7 -0
  4. tf_model.h5 +3 -0
  5. tokenizer.json +0 -0
  6. tokenizer_config.json +57 -0
  7. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: Kikia26/FineTunePubMedBertWithTensorflowKeras
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+ results: []
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+ ---
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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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+
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+ # Kikia26/FineTunePubMedBertWithTensorflowKeras
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+
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+ This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 1.2909
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+ - Validation Loss: 0.7719
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+ - Train Precision: 0.0
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+ - Train Recall: 0.0
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+ - Train F1: 0.0
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+ - Train Accuracy: 0.7813
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+ - Epoch: 0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 100, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
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+ - training_precision: float32
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+
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+ ### Training results
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+
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+ | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
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+ |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
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+ | 1.2909 | 0.7719 | 0.0 | 0.0 | 0.0 | 0.7813 | 0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - TensorFlow 2.14.0
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext",
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+ "architectures": [
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+ "BertForTokenClassification"
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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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+ "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": "I-CONDITION",
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+ "9": "I-INTERVENTION",
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+ "10": "B-TEST"
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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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+ "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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+ "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": 30522
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+ }
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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vocab.txt ADDED
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