Training complete
Browse files- README.md +80 -0
- config.json +194 -0
- model.safetensors +3 -0
- runs/Feb11_06-50-31_f26b9cc97ceb/events.out.tfevents.1739256632.f26b9cc97ceb.467.0 +3 -0
- runs/Feb11_06-51-45_f26b9cc97ceb/events.out.tfevents.1739256706.f26b9cc97ceb.467.1 +3 -0
- runs/Feb11_06-52-47_f26b9cc97ceb/events.out.tfevents.1739256767.f26b9cc97ceb.467.2 +3 -0
- runs/Feb11_06-53-33_f26b9cc97ceb/events.out.tfevents.1739256813.f26b9cc97ceb.467.3 +3 -0
- runs/Feb11_06-53-59_f26b9cc97ceb/events.out.tfevents.1739256839.f26b9cc97ceb.467.4 +3 -0
- runs/Feb11_06-54-57_f26b9cc97ceb/events.out.tfevents.1739256898.f26b9cc97ceb.467.5 +3 -0
- runs/Feb11_06-56-56_f26b9cc97ceb/events.out.tfevents.1739257017.f26b9cc97ceb.467.6 +3 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +61 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: d4data/biomedical-ner-all
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: ner-biomedical-maccrobat2018
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results: []
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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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# ner-biomedical-maccrobat2018
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This model is a fine-tuned version of [d4data/biomedical-ner-all](https://huggingface.co/d4data/biomedical-ner-all) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6384
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- Accuracy: 0.8007
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 2.7438 | 1.0 | 10 | 1.8410 | 0.2970 |
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| 1.4729 | 2.0 | 20 | 1.0655 | 0.5852 |
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| 0.9161 | 3.0 | 30 | 0.7775 | 0.7075 |
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| 0.6509 | 4.0 | 40 | 0.6808 | 0.7477 |
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| 0.4923 | 5.0 | 50 | 0.6315 | 0.7603 |
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| 0.3818 | 6.0 | 60 | 0.6120 | 0.7756 |
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| 0.3096 | 7.0 | 70 | 0.6025 | 0.7742 |
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| 0.2546 | 8.0 | 80 | 0.5992 | 0.7861 |
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| 0.2089 | 9.0 | 90 | 0.6075 | 0.7883 |
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| 0.178 | 10.0 | 100 | 0.6149 | 0.7877 |
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| 0.159 | 11.0 | 110 | 0.6219 | 0.8012 |
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| 0.139 | 12.0 | 120 | 0.6282 | 0.7997 |
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| 0.1239 | 13.0 | 130 | 0.6222 | 0.7970 |
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| 0.1115 | 14.0 | 140 | 0.6311 | 0.7915 |
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| 0.1015 | 15.0 | 150 | 0.6336 | 0.7976 |
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| 0.0958 | 16.0 | 160 | 0.6321 | 0.7955 |
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| 0.0898 | 17.0 | 170 | 0.6352 | 0.7990 |
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| 0.0874 | 18.0 | 180 | 0.6464 | 0.7981 |
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| 0.0841 | 19.0 | 190 | 0.6380 | 0.7992 |
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| 0.0819 | 20.0 | 200 | 0.6384 | 0.8007 |
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### Framework versions
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- Transformers 4.48.2
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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config.json
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{
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"_name_or_path": "d4data/biomedical-ner-all",
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "O",
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"1": "B-Age",
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"2": "I-Age",
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"3": "B-Personal_background",
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"4": "B-Sex",
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"5": "B-History",
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"6": "I-History",
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"7": "B-Sign_symptom",
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"8": "I-Sign_symptom",
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"9": "B-Detailed_description",
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"10": "I-Detailed_description",
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"11": "B-Duration",
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"12": "I-Duration",
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"13": "B-Clinical_event",
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"14": "B-Nonbiological_location",
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"15": "I-Nonbiological_location",
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"16": "B-Biological_structure",
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"17": "B-Activity",
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"18": "I-Activity",
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"19": "B-Diagnostic_procedure",
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"20": "I-Diagnostic_procedure",
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"21": "B-Lab_value",
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"22": "I-Lab_value",
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"23": "B-Outcome",
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"24": "B-Disease_disorder",
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"25": "I-Disease_disorder",
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"26": "I-Biological_structure",
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"27": "B-Severity",
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"28": "I-Severity",
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"29": "B-Texture",
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"30": "I-Texture",
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"31": "B-Therapeutic_procedure",
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"32": "I-Therapeutic_procedure",
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"33": "B-Medication",
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"34": "I-Medication",
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"35": "B-Date",
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"36": "I-Date",
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"37": "B-Frequency",
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"38": "B-Volume",
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"39": "I-Volume",
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"40": "B-Distance",
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"41": "I-Distance",
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"42": "B-Coreference",
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"43": "I-Coreference",
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"44": "I-Clinical_event",
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"45": "B-Subject",
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"46": "I-Subject",
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"47": "B-Family_history",
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"48": "I-Family_history",
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"49": "I-Personal_background",
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"50": "B-Administration",
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"51": "I-Administration",
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"52": "B-Dosage",
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"53": "I-Dosage",
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"54": "B-Other_entity",
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"55": "I-Other_entity",
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"56": "I-Frequency",
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"57": "B-Other_event",
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"58": "I-Other_event",
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"59": "B-Quantitative_concept",
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"60": "B-Occupation",
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"61": "B-Shape",
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"62": "I-Occupation",
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"63": "B-Color",
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"64": "I-Color",
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"65": "B-Area",
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"66": "I-Area",
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"67": "B-Biological_attribute",
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"68": "I-Biological_attribute",
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"69": "I-Outcome",
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"70": "I-Shape",
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"71": "B-Qualitative_concept",
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"72": "B-Time",
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"73": "I-Time",
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"74": "I-Quantitative_concept",
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"75": "I-Qualitative_concept",
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"76": "B-Height",
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"77": "I-Height",
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"78": "B-Weight",
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"79": "I-Weight",
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"80": "I-Sex",
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"81": "B-Mass",
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"82": "I-Mass"
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},
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"initializer_range": 0.02,
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"label2id": {
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"B-Activity": 17,
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"B-Administration": 50,
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"B-Age": 1,
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"B-Area": 65,
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"B-Biological_attribute": 67,
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"B-Biological_structure": 16,
|
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"B-Clinical_event": 13,
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"B-Color": 63,
|
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"B-Coreference": 42,
|
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"B-Date": 35,
|
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+
"B-Detailed_description": 9,
|
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"B-Diagnostic_procedure": 19,
|
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"B-Disease_disorder": 24,
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"B-Distance": 40,
|
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"B-Dosage": 52,
|
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"B-Duration": 11,
|
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+
"B-Family_history": 47,
|
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+
"B-Frequency": 37,
|
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+
"B-Height": 76,
|
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"B-History": 5,
|
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+
"B-Lab_value": 21,
|
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"B-Mass": 81,
|
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+
"B-Medication": 33,
|
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+
"B-Nonbiological_location": 14,
|
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+
"B-Occupation": 60,
|
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+
"B-Other_entity": 54,
|
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+
"B-Other_event": 57,
|
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+
"B-Outcome": 23,
|
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+
"B-Personal_background": 3,
|
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+
"B-Qualitative_concept": 71,
|
128 |
+
"B-Quantitative_concept": 59,
|
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+
"B-Severity": 27,
|
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+
"B-Sex": 4,
|
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+
"B-Shape": 61,
|
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+
"B-Sign_symptom": 7,
|
133 |
+
"B-Subject": 45,
|
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+
"B-Texture": 29,
|
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+
"B-Therapeutic_procedure": 31,
|
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+
"B-Time": 72,
|
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+
"B-Volume": 38,
|
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+
"B-Weight": 78,
|
139 |
+
"I-Activity": 18,
|
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+
"I-Administration": 51,
|
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+
"I-Age": 2,
|
142 |
+
"I-Area": 66,
|
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+
"I-Biological_attribute": 68,
|
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+
"I-Biological_structure": 26,
|
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+
"I-Clinical_event": 44,
|
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+
"I-Color": 64,
|
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+
"I-Coreference": 43,
|
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+
"I-Date": 36,
|
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+
"I-Detailed_description": 10,
|
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+
"I-Diagnostic_procedure": 20,
|
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+
"I-Disease_disorder": 25,
|
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+
"I-Distance": 41,
|
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+
"I-Dosage": 53,
|
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+
"I-Duration": 12,
|
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+
"I-Family_history": 48,
|
156 |
+
"I-Frequency": 56,
|
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+
"I-Height": 77,
|
158 |
+
"I-History": 6,
|
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+
"I-Lab_value": 22,
|
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+
"I-Mass": 82,
|
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+
"I-Medication": 34,
|
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+
"I-Nonbiological_location": 15,
|
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+
"I-Occupation": 62,
|
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+
"I-Other_entity": 55,
|
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+
"I-Other_event": 58,
|
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+
"I-Outcome": 69,
|
167 |
+
"I-Personal_background": 49,
|
168 |
+
"I-Qualitative_concept": 75,
|
169 |
+
"I-Quantitative_concept": 74,
|
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+
"I-Severity": 28,
|
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+
"I-Sex": 80,
|
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+
"I-Shape": 70,
|
173 |
+
"I-Sign_symptom": 8,
|
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+
"I-Subject": 46,
|
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+
"I-Texture": 30,
|
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+
"I-Therapeutic_procedure": 32,
|
177 |
+
"I-Time": 73,
|
178 |
+
"I-Volume": 39,
|
179 |
+
"I-Weight": 79,
|
180 |
+
"O": 0
|
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+
},
|
182 |
+
"max_position_embeddings": 512,
|
183 |
+
"model_type": "distilbert",
|
184 |
+
"n_heads": 12,
|
185 |
+
"n_layers": 6,
|
186 |
+
"pad_token_id": 0,
|
187 |
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"qa_dropout": 0.1,
|
188 |
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"seq_classif_dropout": 0.2,
|
189 |
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"sinusoidal_pos_embds": false,
|
190 |
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"tie_weights_": true,
|
191 |
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"torch_dtype": "float32",
|
192 |
+
"transformers_version": "4.48.2",
|
193 |
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"vocab_size": 30522
|
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}
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model.safetensors
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:a11b57a42b991931e72d27c75204a87b4fdbc5de08179b746eb57434b661951c
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size 265719180
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runs/Feb11_06-50-31_f26b9cc97ceb/events.out.tfevents.1739256632.f26b9cc97ceb.467.0
ADDED
@@ -0,0 +1,3 @@
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+
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tokenizer.json
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tokenizer_config.json
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training_args.bin
ADDED
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vocab.txt
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