---
library_name: transformers
license: apache-2.0
base_model: TurboPascal/ChineseModernBert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner_based_ChineseModernBert_without_phone
  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. -->

# ner_based_ChineseModernBert_without_phone

This model is a fine-tuned version of [TurboPascal/ChineseModernBert](https://huggingface.co/TurboPascal/ChineseModernBert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0239
- Precision: 0.9365
- Recall: 0.9401
- F1: 0.9383
- Accuracy: 0.9960

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- 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: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 163  | 0.0310          | 0.8354    | 0.8581 | 0.8466 | 0.9907   |
| No log        | 2.0   | 326  | 0.0202          | 0.8915    | 0.9244 | 0.9077 | 0.9942   |
| No log        | 3.0   | 489  | 0.0174          | 0.9211    | 0.9297 | 0.9254 | 0.9953   |
| 0.0784        | 4.0   | 652  | 0.0167          | 0.9226    | 0.9374 | 0.9300 | 0.9956   |
| 0.0784        | 5.0   | 815  | 0.0182          | 0.9305    | 0.9434 | 0.9369 | 0.9959   |
| 0.0784        | 6.0   | 978  | 0.0193          | 0.9329    | 0.9438 | 0.9383 | 0.9960   |
| 0.0046        | 7.0   | 1141 | 0.0220          | 0.9333    | 0.9430 | 0.9381 | 0.9960   |
| 0.0046        | 8.0   | 1304 | 0.0221          | 0.9328    | 0.9437 | 0.9382 | 0.9959   |
| 0.0046        | 9.0   | 1467 | 0.0235          | 0.9320    | 0.9452 | 0.9385 | 0.9960   |
| 0.0011        | 10.0  | 1630 | 0.0239          | 0.9365    | 0.9401 | 0.9383 | 0.9960   |


### Framework versions

- Transformers 4.54.0
- Pytorch 2.7.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4