End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: ner_model_ep1
+  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_model_ep1
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3469
+-  allergy Name F1: 0.7059
+-  allergy Name Pres: 0.7326
+-  allergy Name Rec: 0.6811
+-  cancer F1: 0.6499
+-  cancer Pres: 0.6837
+-  cancer Rec: 0.6192
+-  chronic Disease F1: 0.7431
+-  chronic Disease Pres: 0.7462
+-  chronic Disease Rec: 0.7400
+-  treatment F1: 0.7572
+-  treatmen Prest: 0.7680
+-  treatment Rec: 0.7468
+- Over All Precision: 0.7475
+- Over All Recall: 0.7237
+- Over All F1: 0.7354
+- Over All Accuracy: 0.8824
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |  allergy Name F1 |  allergy Name Pres |  allergy Name Rec |  cancer F1 |  cancer Pres |  cancer Rec |  chronic Disease F1 |  chronic Disease Pres |  chronic Disease Rec |  treatment F1 |  treatmen Prest |  treatment Rec | Over All Precision | Over All Recall | Over All F1 | Over All Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------------:|:------------------:|:-----------------:|:----------:|:------------:|:-----------:|:-------------------:|:---------------------:|:--------------------:|:-------------:|:---------------:|:--------------:|:------------------:|:---------------:|:-----------:|:-----------------:|
+| 0.5799        | 1.0   | 368  | 0.4111          | 0.2933           | 0.825              | 0.1784            | 0.5345     | 0.5010       | 0.5728      | 0.6044              | 0.6269                | 0.5834               | 0.6718        | 0.6294          | 0.7204         | 0.6084             | 0.6379          | 0.6228      | 0.8467            |
+| 0.3846        | 2.0   | 736  | 0.3624          | 0.6618           | 0.6054             | 0.7297            | 0.6057     | 0.6025       | 0.6088      | 0.6553              | 0.6925                | 0.6219               | 0.7153        | 0.7450          | 0.6879         | 0.7                | 0.6537          | 0.6761      | 0.8642            |
+| 0.3069        | 3.0   | 1104 | 0.3516          | 0.6801           | 0.7284             | 0.6378            | 0.6316     | 0.6489       | 0.6152      | 0.6994              | 0.7227                | 0.6775               | 0.7317        | 0.7368          | 0.7267         | 0.7187             | 0.6906          | 0.7044      | 0.8733            |
+| 0.2571        | 4.0   | 1472 | 0.3492          | 0.6807           | 0.7687             | 0.6108            | 0.6472     | 0.6867       | 0.612       | 0.7239              | 0.7276                | 0.7201               | 0.7456        | 0.7548          | 0.7366         | 0.7358             | 0.7092          | 0.7222      | 0.8779            |
+| 0.2276        | 5.0   | 1840 | 0.3469          | 0.7059           | 0.7326             | 0.6811            | 0.6499     | 0.6837       | 0.6192      | 0.7431              | 0.7462                | 0.7400               | 0.7572        | 0.7680          | 0.7468         | 0.7475             | 0.7237          | 0.7354      | 0.8824            |
+
+
+### 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": "distilbert/distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForTokenClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "O",
+    "1": "B-treatment",
+    "2": "B-chronic_disease",
+    "3": "I-chronic_disease",
+    "4": "I-treatment",
+    "5": "B-cancer",
+    "6": "I-cancer",
+    "7": "B-allergy_name",
+    "8": "I-allergy_name"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "B-allergy_name": 7,
+    "B-cancer": 5,
+    "B-chronic_disease": 2,
+    "B-treatment": 1,
+    "I-allergy_name": 8,
+    "I-cancer": 6,
+    "I-chronic_disease": 3,
+    "I-treatment": 4,
+    "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": "4.42.4",
+  "vocab_size": 30522
+}

model.safetensors

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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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+      "lstrip": false,
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+      "normalized": false,
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+      "single_word": false,
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+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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