Training complete

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: bert-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. -->
+
+# bert-base-uncased-ner
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0067
+- Cases: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 615}
+- Country: {'precision': 0.988135593220339, 'recall': 0.9898132427843803, 'f1': 0.9889737065309584, 'number': 589}
+- Date: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 73}
+- Deaths: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 428}
+- Virus: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1329}
+- Overall Precision: 0.9977
+- Overall Recall: 0.9980
+- Overall F1: 0.9979
+- Overall Accuracy: 0.9988
+
+## 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                                                       | Deaths                                                                                    | Virus                                                                                                     | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:-----------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| No log        | 1.0   | 291  | 0.0079          | {'precision': 0.9967585089141004, 'recall': 1.0, 'f1': 0.9983766233766234, 'number': 615} | {'precision': 0.9862778730703259, 'recall': 0.9762308998302207, 'f1': 0.9812286689419796, 'number': 589} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 73} | {'precision': 1.0, 'recall': 0.9929906542056075, 'f1': 0.9964830011723329, 'number': 428} | {'precision': 0.9992469879518072, 'recall': 0.9984951091045899, 'f1': 0.9988709070380127, 'number': 1329} | 0.9964            | 0.9937         | 0.9950     | 0.9982           |
+| 0.0793        | 2.0   | 582  | 0.0029          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 615}                               | {'precision': 0.9865092748735245, 'recall': 0.9932088285229203, 'f1': 0.9898477157360406, 'number': 589} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 73} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 428}                               | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1329}                                              | 0.9974            | 0.9987         | 0.9980     | 0.9990           |
+| 0.0793        | 3.0   | 873  | 0.0029          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 615}                               | {'precision': 0.9864406779661017, 'recall': 0.9881154499151104, 'f1': 0.9872773536895674, 'number': 589} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 73} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 428}                               | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1329}                                              | 0.9974            | 0.9977         | 0.9975     | 0.9992           |
+| 0.0059        | 4.0   | 1164 | 0.0062          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 615}                               | {'precision': 0.988135593220339, 'recall': 0.9898132427843803, 'f1': 0.9889737065309584, 'number': 589}  | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 73} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 428}                               | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1329}                                              | 0.9977            | 0.9980         | 0.9979     | 0.9988           |
+| 0.0059        | 5.0   | 1455 | 0.0067          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 615}                               | {'precision': 0.988135593220339, 'recall': 0.9898132427843803, 'f1': 0.9889737065309584, 'number': 589}  | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 73} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 428}                               | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1329}                                              | 0.9977            | 0.9980         | 0.9979     | 0.9988           |
+
+
+### 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,
+  "gradient_checkpointing": false,
+  "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-COUNTRY",
+    "6": "I-VIRUS",
+    "7": "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-COUNTRY": 5,
+    "I-VIRUS": 6,
+    "O": 7
+  },
+  "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": 30522
+}

model.safetensors

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+oid sha256:9f5dee3465890e8c9c829e0f01787c9ebe01db0aed18c8a614e16b97d0edb924
+size 435614544

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
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "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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+size 5304