End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: sentence-transformers/all-MiniLM-L12-v2
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: allminidatamarker
+  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. -->
+
+# allminidatamarker
+
+This model is a fine-tuned version of [sentence-transformers/all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5075
+- Precision: 0.2471
+- Recall: 0.7698
+- F1: 0.3741
+- Accuracy: 0.8521
+
+## 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
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 1.0925        | 1.0   | 38   | 0.6276          | 0.0122    | 0.0719 | 0.0208 | 0.8231   |
+| 1.0925        | 2.0   | 76   | 0.3662          | 0.0677    | 0.4245 | 0.1167 | 0.8200   |
+| 0.5958        | 3.0   | 114  | 0.4129          | 0.1643    | 0.7338 | 0.2684 | 0.8132   |
+| 0.5958        | 4.0   | 152  | 0.4021          | 0.2243    | 0.8777 | 0.3572 | 0.8240   |
+| 0.5958        | 5.0   | 190  | 0.3689          | 0.2495    | 0.8921 | 0.3899 | 0.8458   |
+| 0.1649        | 6.0   | 228  | 0.3811          | 0.2597    | 0.8201 | 0.3945 | 0.8573   |
+| 0.1649        | 7.0   | 266  | 0.4279          | 0.2806    | 0.8417 | 0.4209 | 0.8602   |
+| 0.0941        | 8.0   | 304  | 0.4482          | 0.2322    | 0.7050 | 0.3494 | 0.8535   |
+| 0.0941        | 9.0   | 342  | 0.4992          | 0.1965    | 0.5612 | 0.2910 | 0.8483   |
+| 0.0941        | 10.0  | 380  | 0.5075          | 0.2471    | 0.7698 | 0.3741 | 0.8521   |
+
+
+### Framework versions
+
+- Transformers 4.53.2
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.2

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": 384,
+  "id2label": {
+    "0": "O",
+    "1": "B-ENTITY",
+    "2": "I-ENTITY"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "B-ENTITY": 1,
+    "I-ENTITY": 2,
+    "O": 0
+  },
+  "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": "4.53.2",
+  "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": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "lstrip": false,
+    "normalized": false,
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+    "lstrip": false,
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+    "rstrip": false,
+    "single_word": false
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+    "lstrip": false,
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+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "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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+    "100": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
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+      "single_word": false,
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+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "label_all_tokens": true,
+  "mask_token": "[MASK]",
+  "max_length": 128,
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

training_args.bin

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