End of training

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: section-classification
+  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. -->
+
+# section-classification
+
+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: 1.2353
+- Accuracy: 0.7392
+- Precision: 0.6439
+- Recall: 0.7392
+- F1: 0.6845
+
+## 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: 2e-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
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 434  | 1.2791          | 0.6882   | 0.6056    | 0.6882 | 0.6399 |
+| 1.3149        | 2.0   | 868  | 1.2669          | 0.7204   | 0.6216    | 0.7204 | 0.6674 |
+| 1.2335        | 3.0   | 1302 | 1.2441          | 0.7419   | 0.6477    | 0.7419 | 0.6869 |
+| 1.2607        | 4.0   | 1736 | 1.2353          | 0.7392   | 0.6439    | 0.7392 | 0.6845 |
+
+
+### 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,
+  "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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