End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-uncased-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-base-uncased-finetuned-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: 0.7238
+- Precision: 0.3864
+- Recall: 0.2742
+- F1: 0.3208
+- Accuracy: 0.9134
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 25
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 16   | 0.6017          | 0.4286    | 0.2258 | 0.2958 | 0.9187   |
+| No log        | 2.0   | 32   | 0.6134          | 0.3311    | 0.2688 | 0.2967 | 0.9075   |
+| No log        | 3.0   | 48   | 0.5969          | 0.3525    | 0.2634 | 0.3015 | 0.9096   |
+| No log        | 4.0   | 64   | 0.6446          | 0.3208    | 0.2742 | 0.2957 | 0.9071   |
+| No log        | 5.0   | 80   | 0.6219          | 0.4182    | 0.2473 | 0.3108 | 0.9176   |
+| No log        | 6.0   | 96   | 0.6519          | 0.3401    | 0.2688 | 0.3003 | 0.9103   |
+| No log        | 7.0   | 112  | 0.6576          | 0.3551    | 0.2634 | 0.3025 | 0.9120   |
+| No log        | 8.0   | 128  | 0.6534          | 0.3676    | 0.2688 | 0.3106 | 0.9106   |
+| No log        | 9.0   | 144  | 0.6522          | 0.3732    | 0.2849 | 0.3232 | 0.9124   |
+| No log        | 10.0  | 160  | 0.6879          | 0.3503    | 0.2957 | 0.3207 | 0.9078   |
+| No log        | 11.0  | 176  | 0.6825          | 0.3696    | 0.2742 | 0.3148 | 0.9124   |
+| No log        | 12.0  | 192  | 0.7115          | 0.3732    | 0.2849 | 0.3232 | 0.9120   |
+| No log        | 13.0  | 208  | 0.7013          | 0.3984    | 0.2742 | 0.3248 | 0.9138   |
+| No log        | 14.0  | 224  | 0.7016          | 0.3732    | 0.2849 | 0.3232 | 0.9117   |
+| No log        | 15.0  | 240  | 0.7313          | 0.3643    | 0.2742 | 0.3129 | 0.9110   |
+| No log        | 16.0  | 256  | 0.7267          | 0.3442    | 0.2849 | 0.3118 | 0.9082   |
+| No log        | 17.0  | 272  | 0.7159          | 0.3624    | 0.2903 | 0.3224 | 0.9096   |
+| No log        | 18.0  | 288  | 0.6946          | 0.3542    | 0.2742 | 0.3091 | 0.9099   |
+| No log        | 19.0  | 304  | 0.7017          | 0.3852    | 0.2796 | 0.3240 | 0.9127   |
+| No log        | 20.0  | 320  | 0.7229          | 0.3467    | 0.2796 | 0.3095 | 0.9089   |
+| No log        | 21.0  | 336  | 0.7188          | 0.3817    | 0.2688 | 0.3155 | 0.9124   |
+| No log        | 22.0  | 352  | 0.7269          | 0.3669    | 0.2742 | 0.3138 | 0.9110   |
+| No log        | 23.0  | 368  | 0.7248          | 0.3714    | 0.2796 | 0.3190 | 0.9113   |
+| No log        | 24.0  | 384  | 0.7235          | 0.3835    | 0.2742 | 0.3197 | 0.9131   |
+| No log        | 25.0  | 400  | 0.7238          | 0.3864    | 0.2742 | 0.3208 | 0.9134   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "google-bert/bert-base-uncased",
+  "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": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9",
+    "10": "LABEL_10",
+    "11": "LABEL_11",
+    "12": "LABEL_12",
+    "13": "LABEL_13",
+    "14": "LABEL_14"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
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+    "LABEL_10": 10,
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+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8,
+    "LABEL_9": 9
+  },
+  "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": "4.41.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "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": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+  "add_prefix_space": true,
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+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "single_word": false,
+      "special": true
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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": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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