Training complete

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: d4data/biomedical-ner-all
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: ner-biomedical-maccrobat2018
+  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. -->
+
+# ner-biomedical-maccrobat2018
+
+This model is a fine-tuned version of [d4data/biomedical-ner-all](https://huggingface.co/d4data/biomedical-ner-all) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5565
+- Accuracy: 0.7909
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.641         | 1.0   | 10   | 1.5081          | 0.3577   |
+| 1.338         | 2.0   | 20   | 0.9042          | 0.6165   |
+| 0.877         | 3.0   | 30   | 0.6942          | 0.7081   |
+| 0.6363        | 4.0   | 40   | 0.5950          | 0.7520   |
+| 0.4868        | 5.0   | 50   | 0.5515          | 0.7573   |
+| 0.3798        | 6.0   | 60   | 0.5296          | 0.7688   |
+| 0.3047        | 7.0   | 70   | 0.5217          | 0.7825   |
+| 0.2521        | 8.0   | 80   | 0.5290          | 0.7788   |
+| 0.2123        | 9.0   | 90   | 0.5283          | 0.7852   |
+| 0.1819        | 10.0  | 100  | 0.5309          | 0.7880   |
+| 0.1585        | 11.0  | 110  | 0.5345          | 0.7835   |
+| 0.1388        | 12.0  | 120  | 0.5430          | 0.7823   |
+| 0.1235        | 13.0  | 130  | 0.5350          | 0.7871   |
+| 0.1128        | 14.0  | 140  | 0.5406          | 0.7882   |
+| 0.1036        | 15.0  | 150  | 0.5561          | 0.7873   |
+| 0.0985        | 16.0  | 160  | 0.5603          | 0.7887   |
+| 0.0924        | 17.0  | 170  | 0.5559          | 0.7894   |
+| 0.0883        | 18.0  | 180  | 0.5575          | 0.7909   |
+| 0.0832        | 19.0  | 190  | 0.5545          | 0.7910   |
+| 0.0843        | 20.0  | 200  | 0.5565          | 0.7909   |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+{
+  "_name_or_path": "d4data/biomedical-ner-all",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForTokenClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "O",
+    "1": "B-Age",
+    "2": "I-Age",
+    "3": "B-History",
+    "4": "I-History",
+    "5": "B-Sex",
+    "6": "B-Clinical_event",
+    "7": "B-Sign_symptom",
+    "8": "B-Duration",
+    "9": "I-Duration",
+    "10": "I-Sign_symptom",
+    "11": "B-Coreference",
+    "12": "B-Frequency",
+    "13": "I-Frequency",
+    "14": "B-Detailed_description",
+    "15": "I-Detailed_description",
+    "16": "B-Biological_structure",
+    "17": "I-Biological_structure",
+    "18": "B-Lab_value",
+    "19": "I-Lab_value",
+    "20": "B-Diagnostic_procedure",
+    "21": "I-Diagnostic_procedure",
+    "22": "B-Disease_disorder",
+    "23": "I-Disease_disorder",
+    "24": "B-Therapeutic_procedure",
+    "25": "I-Therapeutic_procedure",
+    "26": "I-Clinical_event",
+    "27": "B-Date",
+    "28": "I-Date",
+    "29": "I-Coreference",
+    "30": "B-Texture",
+    "31": "I-Texture",
+    "32": "B-Severity",
+    "33": "B-Biological_attribute",
+    "34": "I-Biological_attribute",
+    "35": "B-Activity",
+    "36": "I-Activity",
+    "37": "B-Shape",
+    "38": "I-Shape",
+    "39": "B-Color",
+    "40": "I-Color",
+    "41": "B-Outcome",
+    "42": "I-Outcome",
+    "43": "B-Personal_background",
+    "44": "B-Medication",
+    "45": "I-Medication",
+    "46": "B-Dosage",
+    "47": "I-Dosage",
+    "48": "B-Nonbiological_location",
+    "49": "I-Severity",
+    "50": "B-Other_event",
+    "51": "I-Other_event",
+    "52": "B-Administration",
+    "53": "I-Administration",
+    "54": "I-Personal_background",
+    "55": "I-Nonbiological_location",
+    "56": "B-Occupation",
+    "57": "B-Other_entity",
+    "58": "I-Other_entity",
+    "59": "B-Distance",
+    "60": "I-Distance",
+    "61": "B-Time",
+    "62": "I-Time",
+    "63": "B-Area",
+    "64": "I-Area",
+    "65": "B-Family_history",
+    "66": "I-Family_history",
+    "67": "B-Subject",
+    "68": "I-Subject",
+    "69": "B-Volume",
+    "70": "I-Volume",
+    "71": "B-Quantitative_concept",
+    "72": "I-Quantitative_concept",
+    "73": "B-Height",
+    "74": "I-Height",
+    "75": "B-Weight",
+    "76": "I-Weight",
+    "77": "B-Qualitative_concept",
+    "78": "I-Qualitative_concept",
+    "79": "I-Occupation",
+    "80": "I-Sex",
+    "81": "B-Mass",
+    "82": "I-Mass"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "B-Activity": 35,
+    "B-Administration": 52,
+    "B-Age": 1,
+    "B-Area": 63,
+    "B-Biological_attribute": 33,
+    "B-Biological_structure": 16,
+    "B-Clinical_event": 6,
+    "B-Color": 39,
+    "B-Coreference": 11,
+    "B-Date": 27,
+    "B-Detailed_description": 14,
+    "B-Diagnostic_procedure": 20,
+    "B-Disease_disorder": 22,
+    "B-Distance": 59,
+    "B-Dosage": 46,
+    "B-Duration": 8,
+    "B-Family_history": 65,
+    "B-Frequency": 12,
+    "B-Height": 73,
+    "B-History": 3,
+    "B-Lab_value": 18,
+    "B-Mass": 81,
+    "B-Medication": 44,
+    "B-Nonbiological_location": 48,
+    "B-Occupation": 56,
+    "B-Other_entity": 57,
+    "B-Other_event": 50,
+    "B-Outcome": 41,
+    "B-Personal_background": 43,
+    "B-Qualitative_concept": 77,
+    "B-Quantitative_concept": 71,
+    "B-Severity": 32,
+    "B-Sex": 5,
+    "B-Shape": 37,
+    "B-Sign_symptom": 7,
+    "B-Subject": 67,
+    "B-Texture": 30,
+    "B-Therapeutic_procedure": 24,
+    "B-Time": 61,
+    "B-Volume": 69,
+    "B-Weight": 75,
+    "I-Activity": 36,
+    "I-Administration": 53,
+    "I-Age": 2,
+    "I-Area": 64,
+    "I-Biological_attribute": 34,
+    "I-Biological_structure": 17,
+    "I-Clinical_event": 26,
+    "I-Color": 40,
+    "I-Coreference": 29,
+    "I-Date": 28,
+    "I-Detailed_description": 15,
+    "I-Diagnostic_procedure": 21,
+    "I-Disease_disorder": 23,
+    "I-Distance": 60,
+    "I-Dosage": 47,
+    "I-Duration": 9,
+    "I-Family_history": 66,
+    "I-Frequency": 13,
+    "I-Height": 74,
+    "I-History": 4,
+    "I-Lab_value": 19,
+    "I-Mass": 82,
+    "I-Medication": 45,
+    "I-Nonbiological_location": 55,
+    "I-Occupation": 79,
+    "I-Other_entity": 58,
+    "I-Other_event": 51,
+    "I-Outcome": 42,
+    "I-Personal_background": 54,
+    "I-Qualitative_concept": 78,
+    "I-Quantitative_concept": 72,
+    "I-Severity": 49,
+    "I-Sex": 80,
+    "I-Shape": 38,
+    "I-Sign_symptom": 10,
+    "I-Subject": 68,
+    "I-Texture": 31,
+    "I-Therapeutic_procedure": 25,
+    "I-Time": 62,
+    "I-Volume": 70,
+    "I-Weight": 76,
+    "O": 0
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "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": "4.47.1",
+  "vocab_size": 30522
+}

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special_tokens_map.json

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tokenizer_config.json

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+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

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