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-cru
+  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-cru
+
+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: 0.3223
+- Subset Accuracy: 0.3042
+- F1 Macro: 0.3530
+- F1 Micro: 0.4203
+- Precision Macro: 0.3824
+- Recall Macro: 0.3341
+- Roc Auc: 0.8074
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 2025
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- 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: 20
+- 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 |
+|:-------------:|:-------:|:-----:|:---------------:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:-------:|
+| 0.4174        | 0.5737  | 767   | 0.2090          | 0.0             | 0.0      | 0.0      | 0.0             | 0.0          | 0.5932  |
+| 0.1828        | 1.1473  | 1534  | 0.1748          | 0.1320          | 0.0803   | 0.2207   | 0.1575          | 0.0620       | 0.7877  |
+| 0.1663        | 1.7210  | 2301  | 0.1643          | 0.2066          | 0.1822   | 0.3172   | 0.4112          | 0.1480       | 0.8266  |
+| 0.1396        | 2.2947  | 3068  | 0.1635          | 0.2842          | 0.2466   | 0.3875   | 0.4562          | 0.2071       | 0.8290  |
+| 0.1299        | 2.8684  | 3835  | 0.1607          | 0.2926          | 0.2628   | 0.3979   | 0.4435          | 0.2153       | 0.8417  |
+| 0.0911        | 3.4420  | 4602  | 0.1791          | 0.3174          | 0.3135   | 0.4089   | 0.4272          | 0.2707       | 0.8325  |
+| 0.0904        | 4.0157  | 5369  | 0.1812          | 0.3292          | 0.3212   | 0.4156   | 0.3918          | 0.2816       | 0.8305  |
+| 0.0599        | 4.5894  | 6136  | 0.2016          | 0.3217          | 0.3415   | 0.4088   | 0.4062          | 0.3074       | 0.8260  |
+| 0.0617        | 5.1631  | 6903  | 0.2137          | 0.3296          | 0.3433   | 0.4198   | 0.4029          | 0.3095       | 0.8252  |
+| 0.041         | 5.7367  | 7670  | 0.2223          | 0.3171          | 0.3360   | 0.4068   | 0.3899          | 0.3036       | 0.8192  |
+| 0.0454        | 6.3104  | 8437  | 0.2336          | 0.3213          | 0.3520   | 0.4188   | 0.4061          | 0.3260       | 0.8154  |
+| 0.0308        | 6.8841  | 9204  | 0.2452          | 0.3134          | 0.3515   | 0.4162   | 0.4116          | 0.3328       | 0.8164  |
+| 0.0297        | 7.4577  | 9971  | 0.2633          | 0.3069          | 0.3440   | 0.4054   | 0.3786          | 0.3308       | 0.8114  |
+| 0.0235        | 8.0314  | 10738 | 0.2637          | 0.3115          | 0.3529   | 0.4178   | 0.3922          | 0.3347       | 0.8141  |
+| 0.0169        | 8.6051  | 11505 | 0.2811          | 0.2937          | 0.3386   | 0.4058   | 0.3737          | 0.3266       | 0.8065  |
+| 0.0175        | 9.1788  | 12272 | 0.2860          | 0.3065          | 0.3577   | 0.4184   | 0.4005          | 0.3381       | 0.8123  |
+| 0.0119        | 9.7524  | 13039 | 0.2919          | 0.3083          | 0.3394   | 0.4118   | 0.3805          | 0.3143       | 0.8128  |
+| 0.0118        | 10.3261 | 13806 | 0.3005          | 0.2954          | 0.3567   | 0.4223   | 0.3666          | 0.3553       | 0.8116  |
+| 0.0089        | 10.8998 | 14573 | 0.3096          | 0.3034          | 0.3507   | 0.4112   | 0.3758          | 0.3372       | 0.8077  |
+| 0.0079        | 11.4734 | 15340 | 0.3186          | 0.3031          | 0.3539   | 0.4143   | 0.3900          | 0.3371       | 0.8070  |
+| 0.0064        | 12.0471 | 16107 | 0.3223          | 0.3042          | 0.3530   | 0.4203   | 0.3824          | 0.3341       | 0.8074  |
+
+
+### 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]"
+}