Model save

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-seq-class-values-no-context_plus
+  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-seq-class-values-no-context_plus
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3789
+- Subset Accuracy: 0.2907
+- F1 Macro: 0.3225
+- F1 Micro: 0.3837
+- Precision Macro: 0.3470
+- Recall Macro: 0.3052
+- Roc Auc: 0.7784
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 2025
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- 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_ratio: 0.1
+- num_epochs: 25
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Subset Accuracy | F1 Macro | F1 Micro | Precision Macro | Recall Macro | Roc Auc |
+|:-------------:|:-----:|:-----:|:---------------:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:-------:|
+| 0.3261        | 1.0   | 767   | 0.1848          | 0.0358          | 0.0273   | 0.0682   | 0.1322          | 0.0165       | 0.7523  |
+| 0.1653        | 2.0   | 1534  | 0.1687          | 0.2000          | 0.1740   | 0.3048   | 0.3058          | 0.1429       | 0.8180  |
+| 0.1422        | 3.0   | 2301  | 0.1700          | 0.2427          | 0.2509   | 0.3398   | 0.4408          | 0.1957       | 0.8239  |
+| 0.1091        | 4.0   | 3068  | 0.1864          | 0.3055          | 0.2801   | 0.3921   | 0.4249          | 0.2469       | 0.8166  |
+| 0.0806        | 5.0   | 3835  | 0.2045          | 0.3021          | 0.2926   | 0.3841   | 0.3993          | 0.2540       | 0.8079  |
+| 0.0542        | 6.0   | 4602  | 0.2328          | 0.2992          | 0.2961   | 0.3785   | 0.3630          | 0.2644       | 0.7991  |
+| 0.0434        | 7.0   | 5369  | 0.2475          | 0.2842          | 0.3076   | 0.3845   | 0.3510          | 0.2955       | 0.7982  |
+| 0.0311        | 8.0   | 6136  | 0.2661          | 0.2919          | 0.3236   | 0.3904   | 0.3442          | 0.3168       | 0.7920  |
+| 0.025         | 9.0   | 6903  | 0.2812          | 0.2844          | 0.3201   | 0.3858   | 0.3441          | 0.3085       | 0.7878  |
+| 0.0186        | 10.0  | 7670  | 0.3123          | 0.2826          | 0.3246   | 0.3879   | 0.3432          | 0.3220       | 0.7827  |
+| 0.0152        | 11.0  | 8437  | 0.3156          | 0.2689          | 0.3217   | 0.3774   | 0.3374          | 0.3157       | 0.7828  |
+| 0.0109        | 12.0  | 9204  | 0.3380          | 0.2856          | 0.3127   | 0.3800   | 0.3410          | 0.2994       | 0.7785  |
+| 0.0095        | 13.0  | 9971  | 0.3636          | 0.2684          | 0.3187   | 0.3783   | 0.3385          | 0.3140       | 0.7699  |
+| 0.0063        | 14.0  | 10738 | 0.3684          | 0.2835          | 0.3206   | 0.3807   | 0.3478          | 0.3049       | 0.7755  |
+| 0.0054        | 15.0  | 11505 | 0.3789          | 0.2907          | 0.3225   | 0.3837   | 0.3470          | 0.3052       | 0.7784  |
+
+
+### Framework versions
+
+- Transformers 4.53.2
+- Pytorch 2.6.0+cu124
+- Datasets 2.14.4
+- Tokenizers 0.21.2

model.safetensors

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 size 438010940

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]"
+}