task-t3

README.md

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+---
+license: apache-2.0
+base_model: KpRT/task-t2
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: task-t3
+  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. -->
+
+# task-t3
+
+This model is a fine-tuned version of [KpRT/task-t2](https://huggingface.co/KpRT/task-t2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3985
+- F1: 0.7669
+- Chronic Disease F1: 0.7755
+- Chronic Disease Num: 2507
+- Cancer F1: 0.7152
+- Cancer Num: 753
+- Allergy F1: 0.7833
+- Allergy Num: 271
+- Treatment F1: 0.7715
+- Treatment Num: 2963
+- Other F1: 0
+- Other Num: 0
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | F1     | Chronic Disease F1 | Chronic Disease Num | Cancer F1 | Cancer Num | Allergy F1 | Allergy Num | Treatment F1 | Treatment Num | Other F1 | Other Num |
+|:-------------:|:------:|:----:|:---------------:|:------:|:------------------:|:-------------------:|:---------:|:----------:|:----------:|:-----------:|:------------:|:-------------:|:--------:|:---------:|
+| 0.236         | 0.3135 | 100  | 0.4006          | 0.7553 | 0.7577             | 2507                | 0.7027    | 753        | 0.7767     | 271         | 0.7650       | 2963          | 0        | 0         |
+| 0.2141        | 0.6270 | 200  | 0.4293          | 0.7513 | 0.7662             | 2507                | 0.6703    | 753        | 0.7850     | 271         | 0.7577       | 2963          | 0        | 0         |
+| 0.2483        | 0.9404 | 300  | 0.4024          | 0.7628 | 0.7710             | 2507                | 0.6994    | 753        | 0.7765     | 271         | 0.7712       | 2963          | 0        | 0         |
+| 0.19          | 1.2539 | 400  | 0.4005          | 0.7666 | 0.7764             | 2507                | 0.7010    | 753        | 0.8069     | 271         | 0.7720       | 2963          | 0        | 0         |
+| 0.1997        | 1.5674 | 500  | 0.3986          | 0.7698 | 0.7786             | 2507                | 0.7137    | 753        | 0.7946     | 271         | 0.7750       | 2963          | 0        | 0         |
+| 0.2297        | 1.8809 | 600  | 0.3985          | 0.7669 | 0.7755             | 2507                | 0.7152    | 753        | 0.7833     | 271         | 0.7715       | 2963          | 0        | 0         |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "KpRT/task-t2",
+  "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-treatment",
+    "2": "I-treatment",
+    "3": "B-chronic_disease",
+    "4": "I-chronic_disease",
+    "5": "B-cancer",
+    "6": "I-cancer",
+    "7": "B-allergy",
+    "8": "I-allergy",
+    "9": "B-other",
+    "10": "I-other"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-allergy_name": 7,
+    "B-cancer": 5,
+    "B-chronic_disease": 3,
+    "B-other": 9,
+    "B-treatment": 1,
+    "I-allergy_name": 8,
+    "I-cancer": 6,
+    "I-chronic_disease": 4,
+    "I-other": 10,
+    "I-treatment": 2,
+    "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": "4.42.4",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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runs/Jul21_07-00-42_5891dff67884/events.out.tfevents.1721545244.5891dff67884.2327.4

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special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
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+    "single_word": false
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+    "single_word": false
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+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

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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+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
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+      "single_word": false,
+      "special": true
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+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "max_length": 512,
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

training_args.bin

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