Training complete

README.md

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+---
+library_name: transformers
+base_model: allenai/scibert_scivocab_uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: scibert-base-uncased-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. -->
+
+# scibert-base-uncased-ner
+
+This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0104
+- Cases: {'precision': 0.9827586206896551, 'recall': 0.9827586206896551, 'f1': 0.9827586206896551, 'number': 464}
+- Country: {'precision': 0.9981378026070763, 'recall': 0.9981378026070763, 'f1': 0.9981378026070763, 'number': 537}
+- Date: {'precision': 0.9811320754716981, 'recall': 0.9879101899827288, 'f1': 0.9845094664371773, 'number': 579}
+- Virus: {'precision': 0.9944954128440368, 'recall': 0.9963235294117647, 'f1': 0.9954086317722682, 'number': 544}
+- Overall Precision: 0.9892
+- Overall Recall: 0.9915
+- Overall F1: 0.9904
+- Overall Accuracy: 0.9967
+
+## 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
+- 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Cases                                                                                                    | Country                                                                                                  | Date                                                                                                     | Virus                                                                                                    | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| No log        | 1.0   | 291  | 0.0217          | {'precision': 0.9393305439330544, 'recall': 0.9676724137931034, 'f1': 0.9532908704883226, 'number': 464} | {'precision': 0.9981378026070763, 'recall': 0.9981378026070763, 'f1': 0.9981378026070763, 'number': 537} | {'precision': 0.9571183533447685, 'recall': 0.9637305699481865, 'f1': 0.9604130808950087, 'number': 579} | {'precision': 0.9908256880733946, 'recall': 0.9926470588235294, 'f1': 0.9917355371900827, 'number': 544} | 0.9720            | 0.9807         | 0.9763     | 0.9947           |
+| 0.0071        | 2.0   | 582  | 0.0076          | {'precision': 0.9778270509977827, 'recall': 0.9504310344827587, 'f1': 0.9639344262295082, 'number': 464} | {'precision': 0.9944341372912802, 'recall': 0.9981378026070763, 'f1': 0.996282527881041, 'number': 537}  | {'precision': 0.975736568457539, 'recall': 0.9723661485319517, 'f1': 0.9740484429065744, 'number': 579}  | {'precision': 0.9908088235294118, 'recall': 0.9908088235294118, 'f1': 0.9908088235294118, 'number': 544} | 0.9848            | 0.9788         | 0.9818     | 0.9973           |
+| 0.0071        | 3.0   | 873  | 0.0151          | {'precision': 0.9827586206896551, 'recall': 0.9827586206896551, 'f1': 0.9827586206896551, 'number': 464} | {'precision': 0.9981378026070763, 'recall': 0.9981378026070763, 'f1': 0.9981378026070763, 'number': 537} | {'precision': 0.9776632302405498, 'recall': 0.9827288428324698, 'f1': 0.9801894918173987, 'number': 579} | {'precision': 0.9944954128440368, 'recall': 0.9963235294117647, 'f1': 0.9954086317722682, 'number': 544} | 0.9883            | 0.9901         | 0.9892     | 0.9967           |
+| 0.0028        | 4.0   | 1164 | 0.0105          | {'precision': 0.9869281045751634, 'recall': 0.9762931034482759, 'f1': 0.981581798483207, 'number': 464}  | {'precision': 0.9944341372912802, 'recall': 0.9981378026070763, 'f1': 0.996282527881041, 'number': 537}  | {'precision': 0.9793459552495697, 'recall': 0.9827288428324698, 'f1': 0.9810344827586207, 'number': 579} | {'precision': 0.9944954128440368, 'recall': 0.9963235294117647, 'f1': 0.9954086317722682, 'number': 544} | 0.9887            | 0.9887         | 0.9887     | 0.9968           |
+| 0.0028        | 5.0   | 1455 | 0.0104          | {'precision': 0.9827586206896551, 'recall': 0.9827586206896551, 'f1': 0.9827586206896551, 'number': 464} | {'precision': 0.9981378026070763, 'recall': 0.9981378026070763, 'f1': 0.9981378026070763, 'number': 537} | {'precision': 0.9811320754716981, 'recall': 0.9879101899827288, 'f1': 0.9845094664371773, 'number': 579} | {'precision': 0.9944954128440368, 'recall': 0.9963235294117647, 'f1': 0.9954086317722682, 'number': 544} | 0.9892            | 0.9915         | 0.9904     | 0.9967           |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.5.1+cu121
+- Datasets 3.5.0
+- Tokenizers 0.21.1

config.json

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+{
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "B-CASES",
+    "1": "B-COUNTRY",
+    "2": "B-DATE",
+    "3": "B-DEATHS",
+    "4": "B-VIRUS",
+    "5": "I-CASES",
+    "6": "I-COUNTRY",
+    "7": "I-DATE",
+    "8": "I-DEATHS",
+    "9": "I-VIRUS",
+    "10": "O"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-CASES": 0,
+    "B-COUNTRY": 1,
+    "B-DATE": 2,
+    "B-DEATHS": 3,
+    "B-VIRUS": 4,
+    "I-CASES": 5,
+    "I-COUNTRY": 6,
+    "I-DATE": 7,
+    "I-DEATHS": 8,
+    "I-VIRUS": 9,
+    "O": 10
+  },
+  "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": "4.51.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31090
+}

model.safetensors

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+oid sha256:8c7a2a4a7357ea8eb2bfbe96a1ff101d717b273f7c7d8b1aab3e4f5604706a61
+size 437368668

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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+    "101": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "102": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
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+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+    "104": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "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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+oid sha256:bfdd7abedb776e51ee247a6d32ee63408f14b8dd25ff0522cd6e28935ef54113
+size 5304