End of training

README.md

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+---
+library_name: transformers
+base_model: dmis-lab/biobert-base-cased-v1.2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: BioBert_pubHealth
+  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. -->
+
+# BioBert_pubHealth
+
+This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6765
+- Accuracy: 0.796
+- Auc: 0.886
+- Precision: 0.861
+- Recall: 0.793
+- F1: 0.825
+- F1-macro: 0.791
+- F1-micro: 0.796
+- F1-weighted: 0.798
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- 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: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Auc   | Precision | Recall | F1    | F1-macro | F1-micro | F1-weighted |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:-----:|:---------:|:------:|:-----:|:--------:|:--------:|:-----------:|
+| 0.5286        | 0.3960 | 100  | 0.4608          | 0.769    | 0.855 | 0.847     | 0.756  | 0.799 | 0.764    | 0.769    | 0.771       |
+| 0.4399        | 0.7921 | 200  | 0.4506          | 0.787    | 0.871 | 0.861     | 0.775  | 0.815 | 0.782    | 0.787    | 0.789       |
+| 0.3929        | 1.1861 | 300  | 0.4363          | 0.791    | 0.878 | 0.829     | 0.826  | 0.828 | 0.781    | 0.791    | 0.791       |
+| 0.368         | 1.5822 | 400  | 0.4003          | 0.797    | 0.884 | 0.881     | 0.77   | 0.822 | 0.794    | 0.797    | 0.8         |
+| 0.3503        | 1.9782 | 500  | 0.4075          | 0.794    | 0.888 | 0.847     | 0.806  | 0.826 | 0.787    | 0.794    | 0.795       |
+| 0.2828        | 2.3723 | 600  | 0.4678          | 0.798    | 0.888 | 0.898     | 0.753  | 0.819 | 0.796    | 0.798    | 0.801       |
+| 0.2647        | 2.7683 | 700  | 0.4296          | 0.796    | 0.89  | 0.893     | 0.755  | 0.818 | 0.793    | 0.796    | 0.799       |
+| 0.2197        | 3.1624 | 800  | 0.5130          | 0.798    | 0.889 | 0.862     | 0.795  | 0.827 | 0.793    | 0.798    | 0.8         |
+| 0.1739        | 3.5584 | 900  | 0.5262          | 0.8      | 0.891 | 0.842     | 0.826  | 0.834 | 0.792    | 0.8      | 0.801       |
+| 0.1517        | 3.9545 | 1000 | 0.6064          | 0.793    | 0.889 | 0.875     | 0.77   | 0.819 | 0.789    | 0.793    | 0.795       |
+| 0.1189        | 4.3485 | 1100 | 0.6257          | 0.793    | 0.887 | 0.848     | 0.803  | 0.825 | 0.786    | 0.793    | 0.795       |
+| 0.0976        | 4.7446 | 1200 | 0.6765          | 0.796    | 0.886 | 0.861     | 0.793  | 0.825 | 0.791    | 0.796    | 0.798       |
+
+
+### Framework versions
+
+- Transformers 4.53.0
+- Pytorch 2.6.0+cu124
+- Datasets 2.14.4
+- Tokenizers 0.21.2

config.json

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+{
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "fake",
+    "1": "real"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "fake": 0,
+    "real": 1
+  },
+  "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",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.53.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

model.safetensors

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+size 433270768

runs/Jul08_08-28-16_7011e4b81f17/events.out.tfevents.1751963325.7011e4b81f17.331.0

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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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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "101": {
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+      "lstrip": false,
+      "normalized": false,
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+      "special": true
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "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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