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Training in progress epoch 0

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  1. README.md +54 -0
  2. config.json +51 -0
  3. special_tokens_map.json +7 -0
  4. tf_model.h5 +3 -0
  5. tokenizer.json +0 -0
  6. tokenizer_config.json +55 -0
  7. vocab.txt +0 -0
README.md ADDED
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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: AlbiGara/bert-finetuned-ner-medical-copy
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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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+ # AlbiGara/bert-finetuned-ner-medical-copy
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+
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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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+ - Train Loss: 0.3099
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+ - Validation Loss: 0.2768
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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': 2e-05, 'decay_steps': 3480, '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 | Epoch |
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+ |:----------:|:---------------:|:-----:|
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+ | 0.3099 | 0.2768 | 0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.1
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+ - TensorFlow 2.15.0
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "bert-base-cased",
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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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+ "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": "O",
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+ "1": "B-DNA",
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+ "2": "I-DNA",
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+ "3": "B-RNA",
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+ "4": "I-RNA",
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+ "5": "B-cell_line",
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+ "6": "I-cell_line",
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+ "7": "B-cell_type",
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+ "8": "I-cell_type",
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+ "9": "B-protein",
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+ "10": "I-protein"
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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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+ "B-DNA": 1,
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+ "B-RNA": 3,
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+ "B-cell_line": 5,
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+ "B-cell_type": 7,
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+ "B-protein": 9,
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+ "I-DNA": 2,
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+ "I-RNA": 4,
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+ "I-cell_line": 6,
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+ "I-cell_type": 8,
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+ "I-protein": 10,
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+ "O": 0
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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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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "transformers_version": "4.40.1",
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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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+ "unk_token": "[UNK]"
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ },
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+ "clean_up_tokenization_spaces": true,
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+ "cls_token": "[CLS]",
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+ "do_lower_case": false,
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+ "mask_token": "[MASK]",
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+ "model_max_length": 512,
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+ "pad_token": "[PAD]",
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+ "tokenize_chinese_chars": true,
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+ "tokenizer_class": "BertTokenizer",
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+ "unk_token": "[UNK]"
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+ }
vocab.txt ADDED
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