End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: BAAI/bge-small-en-v1.5
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-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-finetuned-ner
+
+This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0872
+- Precision: 0.9053
+- Recall: 0.9278
+- F1: 0.9164
+- Accuracy: 0.9827
+
+## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0608        | 1.0   | 1252  | 0.0888          | 0.8833    | 0.9068 | 0.8949 | 0.9791   |
+| 0.0481        | 2.0   | 2504  | 0.0822          | 0.8849    | 0.9159 | 0.9001 | 0.9801   |
+| 0.0387        | 3.0   | 3756  | 0.0822          | 0.9000    | 0.9189 | 0.9093 | 0.9816   |
+| 0.0348        | 4.0   | 5008  | 0.0820          | 0.9000    | 0.9238 | 0.9117 | 0.9820   |
+| 0.038         | 5.0   | 6260  | 0.0810          | 0.8979    | 0.9233 | 0.9104 | 0.9818   |
+| 0.0202        | 6.0   | 7512  | 0.0872          | 0.9019    | 0.9249 | 0.9133 | 0.9813   |
+| 0.0147        | 7.0   | 8764  | 0.0894          | 0.9024    | 0.9241 | 0.9131 | 0.9817   |
+| 0.0357        | 8.0   | 10016 | 0.0880          | 0.9038    | 0.9253 | 0.9144 | 0.9822   |
+| 0.0289        | 9.0   | 11268 | 0.0867          | 0.9056    | 0.9278 | 0.9165 | 0.9827   |
+| 0.0115        | 10.0  | 12520 | 0.0872          | 0.9053    | 0.9278 | 0.9164 | 0.9827   |
+
+
+### Framework versions
+
+- Transformers 4.57.3
+- Pytorch 2.9.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1

config.json

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+{
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "id2label": [
+    "B-LOC",
+    "B-MISC",
+    "B-ORG",
+    "B-PER",
+    "I-LOC",
+    "I-MISC",
+    "I-ORG",
+    "I-PER",
+    "O"
+  ],
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "B-LOC": 0,
+    "B-MISC": 1,
+    "B-ORG": 2,
+    "B-PER": 3,
+    "I-LOC": 4,
+    "I-MISC": 5,
+    "I-ORG": 6,
+    "I-PER": 7,
+    "O": 8
+  },
+  "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",
+  "transformers_version": "4.57.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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special_tokens_map.json

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+{
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+    "lstrip": false,
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+    "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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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
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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": 512,
+  "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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