Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distilbert-base-uncased-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      config: conll2003
+      split: validation
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9240632253785785
+    - name: Recall
+      type: recall
+      value: 0.9352276541000112
+    - name: F1
+      type: f1
+      value: 0.9296119203825197
+    - name: Accuracy
+      type: accuracy
+      value: 0.9833034139831922
+---
+
+<!-- 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. -->
+
+# distilbert-base-uncased-finetuned-ner
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0612
+- Precision: 0.9241
+- Recall: 0.9352
+- F1: 0.9296
+- Accuracy: 0.9833
+
+## 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: 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2418        | 1.0   | 878  | 0.0703          | 0.8958    | 0.9178 | 0.9067 | 0.9794   |
+| 0.0513        | 2.0   | 1756 | 0.0604          | 0.9250    | 0.9314 | 0.9282 | 0.9830   |
+| 0.0302        | 3.0   | 2634 | 0.0612          | 0.9241    | 0.9352 | 0.9296 | 0.9833   |
+
+
+### Framework versions
+
+- Transformers 5.3.0
+- Pytorch 2.10.0+cpu
+- Datasets 4.6.1
+- Tokenizers 0.22.2

model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:0c4da63621f599f7ac3ba33344d193bc1ef8316a8216f99d6eb46100ebc6a35e
 size 265491548

tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "id2label": {
+    "0": "O",
+    "1": "B-PER",
+    "2": "I-PER",
+    "3": "B-ORG",
+    "4": "I-ORG",
+    "5": "B-LOC",
+    "6": "I-LOC",
+    "7": "B-MISC",
+    "8": "I-MISC"
+  },
+  "is_local": false,
+  "label2id": {
+    "B-LOC": 5,
+    "B-MISC": 7,
+    "B-ORG": 3,
+    "B-PER": 1,
+    "I-LOC": 6,
+    "I-MISC": 8,
+    "I-ORG": 4,
+    "I-PER": 2,
+    "O": 0
+  },
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "num_labels": 9,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}