bert-section-classification-v5

README.md

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+---
+library_name: transformers
+base_model: medicalai/ClinicalBERT
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bert-section-classification-v5
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bert-section-classification-v5
+
+This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9710
+- Accuracy: 0.8644
+- Precision: 0.8671
+- Recall: 0.8644
+- F1: 0.8642
+
+## 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:
+- learning_rate: 3e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 300
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 370  | 1.3245          | 0.2555   | 0.3090    | 0.2555 | 0.1199 |
+| 1.3542        | 2.0   | 740  | 1.2024          | 0.7319   | 0.8115    | 0.7319 | 0.7163 |
+| 1.2122        | 3.0   | 1110 | 1.1008          | 0.8675   | 0.8756    | 0.8675 | 0.8678 |
+| 1.2122        | 4.0   | 1480 | 1.0275          | 0.8770   | 0.8834    | 0.8770 | 0.8773 |
+| 1.082         | 5.0   | 1850 | 0.9855          | 0.8707   | 0.8751    | 0.8707 | 0.8706 |
+| 1.003         | 6.0   | 2220 | 0.9710          | 0.8644   | 0.8671    | 0.8644 | 0.8642 |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Tokenizers 0.21.1

config.json

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+{
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "Chief Concern and History",
+    "1": "Clinical Findings",
+    "2": "Diagnostic Results",
+    "3": "Past Health and Social History"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "Chief Concern and History": 0,
+    "Clinical Findings": 1,
+    "Diagnostic Results": 2,
+    "Past Health and Social History": 3
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "output_past": true,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3",
+  "vocab_size": 119547
+}

model.safetensors

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+size 541323528

training_args.bin

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