javicorvi/pretoxtm-ner

README.md

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+---
+base_model: dmis-lab/biobert-v1.1
+tags:
+- generated_from_trainer
+model-index:
+- name: pretoxtm-ner
+  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. -->
+
+# pretoxtm-ner
+
+This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2356
+- Study Test: {'precision': 0.8107098381070984, 'recall': 0.9054242002781642, 'f1': 0.8554533508541393, 'number': 719}
+- Manifestation: {'precision': 0.8428571428571429, 'recall': 0.8966565349544073, 'f1': 0.8689248895434463, 'number': 329}
+- Finding: {'precision': 0.7924263674614306, 'recall': 0.7907627711686495, 'f1': 0.7915936952714535, 'number': 1429}
+- Specimen: {'precision': 0.7935064935064935, 'recall': 0.8427586206896551, 'f1': 0.817391304347826, 'number': 725}
+- Dose: {'precision': 0.8894472361809045, 'recall': 0.9315789473684211, 'f1': 0.910025706940874, 'number': 570}
+- Dose Qualification: {'precision': 0.75, 'recall': 0.7368421052631579, 'f1': 0.743362831858407, 'number': 57}
+- Sex: {'precision': 0.9282296650717703, 'recall': 0.9603960396039604, 'f1': 0.9440389294403893, 'number': 202}
+- Group: {'precision': 0.6992481203007519, 'recall': 0.8303571428571429, 'f1': 0.7591836734693878, 'number': 112}
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Study Test                                                                                               | Manifestation                                                                                            | Finding                                                                                                   | Specimen                                                                                                 | Dose                                                                                                     | Dose Qualification                                                                                      | Sex                                                                                                      | Group                                                                                                    |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 257  | 0.2315          | {'precision': 0.7803680981595092, 'recall': 0.8845618915159944, 'f1': 0.8292046936114733, 'number': 719} | {'precision': 0.8481375358166189, 'recall': 0.8996960486322189, 'f1': 0.8731563421828908, 'number': 329} | {'precision': 0.8012618296529969, 'recall': 0.7109867039888034, 'f1': 0.7534297367445311, 'number': 1429} | {'precision': 0.7451456310679612, 'recall': 0.8468965517241379, 'f1': 0.7927695287282118, 'number': 725} | {'precision': 0.9078498293515358, 'recall': 0.9333333333333333, 'f1': 0.9204152249134948, 'number': 570} | {'precision': 0.703125, 'recall': 0.7894736842105263, 'f1': 0.743801652892562, 'number': 57}            | {'precision': 0.9241706161137441, 'recall': 0.9653465346534653, 'f1': 0.9443099273607748, 'number': 202} | {'precision': 0.625, 'recall': 0.8928571428571429, 'f1': 0.7352941176470589, 'number': 112}              |
+| 0.0608        | 2.0   | 514  | 0.2285          | {'precision': 0.803680981595092, 'recall': 0.9109874826147427, 'f1': 0.8539765319426338, 'number': 719}  | {'precision': 0.846820809248555, 'recall': 0.8905775075987842, 'f1': 0.8681481481481481, 'number': 329}  | {'precision': 0.7780040733197556, 'recall': 0.8019594121763471, 'f1': 0.7898001378359754, 'number': 1429} | {'precision': 0.8052631578947368, 'recall': 0.8441379310344828, 'f1': 0.8242424242424241, 'number': 725} | {'precision': 0.9047619047619048, 'recall': 0.9333333333333333, 'f1': 0.9188255613126078, 'number': 570} | {'precision': 0.7368421052631579, 'recall': 0.7368421052631579, 'f1': 0.7368421052631579, 'number': 57} | {'precision': 0.9289099526066351, 'recall': 0.9702970297029703, 'f1': 0.9491525423728814, 'number': 202} | {'precision': 0.6783216783216783, 'recall': 0.8660714285714286, 'f1': 0.7607843137254903, 'number': 112} |
+| 0.0608        | 3.0   | 771  | 0.2356          | {'precision': 0.8107098381070984, 'recall': 0.9054242002781642, 'f1': 0.8554533508541393, 'number': 719} | {'precision': 0.8428571428571429, 'recall': 0.8966565349544073, 'f1': 0.8689248895434463, 'number': 329} | {'precision': 0.7924263674614306, 'recall': 0.7907627711686495, 'f1': 0.7915936952714535, 'number': 1429} | {'precision': 0.7935064935064935, 'recall': 0.8427586206896551, 'f1': 0.817391304347826, 'number': 725}  | {'precision': 0.8894472361809045, 'recall': 0.9315789473684211, 'f1': 0.910025706940874, 'number': 570}  | {'precision': 0.75, 'recall': 0.7368421052631579, 'f1': 0.743362831858407, 'number': 57}                | {'precision': 0.9282296650717703, 'recall': 0.9603960396039604, 'f1': 0.9440389294403893, 'number': 202} | {'precision': 0.6992481203007519, 'recall': 0.8303571428571429, 'f1': 0.7591836734693878, 'number': 112} |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "dmis-lab/biobert-v1.1",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-MANIFESTATION_FINDING",
+    "2": "B-STUDY_TESTCD",
+    "3": "B-DOSE",
+    "4": "I-DOSE",
+    "5": "B-SEX",
+    "6": "I-STUDY_TESTCD",
+    "7": "I-SEX",
+    "8": "B-FINDING",
+    "9": "I-FINDING",
+    "10": "B-SPECIMEN",
+    "11": "I-SPECIMEN",
+    "12": "B-GROUP",
+    "13": "I-GROUP",
+    "14": "I-MANIFESTATION_FINDING",
+    "15": "B-DOSE_QUALIFICATION",
+    "16": "I-DOSE_QUALIFICATION"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-DOSE": 3,
+    "B-DOSE_QUALIFICATION": 15,
+    "B-FINDING": 8,
+    "B-GROUP": 12,
+    "B-MANIFESTATION_FINDING": 1,
+    "B-SEX": 5,
+    "B-SPECIMEN": 10,
+    "B-STUDY_TESTCD": 2,
+    "I-DOSE": 4,
+    "I-DOSE_QUALIFICATION": 16,
+    "I-FINDING": 9,
+    "I-GROUP": 13,
+    "I-MANIFESTATION_FINDING": 14,
+    "I-SEX": 7,
+    "I-SPECIMEN": 11,
+    "I-STUDY_TESTCD": 6,
+    "O": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

pytorch_model.bin

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+size 430998761

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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