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ribhu/clinical-ner-task-1

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: Charangan/MedBERT
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: medbert-clinical-ner
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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 the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # medbert-clinical-ner
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+
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+ This model is a fine-tuned version of [Charangan/MedBERT](https://huggingface.co/Charangan/MedBERT) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3320
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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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+ - learning_rate: 3e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.15
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | No log | 0.9936 | 39 | 0.6504 |
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+ | No log | 1.9873 | 78 | 0.3659 |
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+ | No log | 2.9809 | 117 | 0.3376 |
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+ | No log | 4.0 | 157 | 0.3330 |
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+ | No log | 4.9682 | 195 | 0.3320 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.5.0+cu121
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+ - Tokenizers 0.19.1
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+ "_name_or_path": "Charangan/MedBERT",
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+ ],
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+ "id2label": {
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+ "0": "O",
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+ "1": "B-allergy_name",
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+ "2": "B-cancer",
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+ "3": "B-chronic_disease",
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+ "4": "B-treatment",
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+ "5": "I-allergy_name",
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+ "6": "I-cancer",
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+ "7": "I-chronic_disease",
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+ "8": "I-treatment"
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+ },
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+ "B-treatment": 4,
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+ "I-chronic_disease": 7,
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+ "I-treatment": 8,
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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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+ "position_embedding_type": "absolute",
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+ "type_vocab_size": 2,
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+ }
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