---
license: apache-2.0
base_model: hfl/chinese-roberta-wwm-ext-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: RoBERTa-ext-large-crf-lora-chinese-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. -->

# RoBERTa-ext-large-crf-lora-chinese-finetuned-ner

This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext-large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4056
- Precision: 0.4202
- Recall: 0.5916
- F1: 0.4914
- Accuracy: 0.9456

## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.3615        | 1.0   | 503  | 0.8081          | 0.1274    | 0.1568 | 0.1406 | 0.9028   |
| 0.702         | 2.0   | 1006 | 0.5824          | 0.2954    | 0.4194 | 0.3467 | 0.9261   |
| 0.5585        | 3.0   | 1509 | 0.5107          | 0.3305    | 0.4922 | 0.3955 | 0.9323   |
| 0.4959        | 4.0   | 2012 | 0.4654          | 0.3716    | 0.5274 | 0.4360 | 0.9377   |
| 0.4614        | 5.0   | 2515 | 0.4427          | 0.3880    | 0.5493 | 0.4548 | 0.9399   |
| 0.4381        | 6.0   | 3018 | 0.4292          | 0.3996    | 0.5657 | 0.4684 | 0.9420   |
| 0.4233        | 7.0   | 3521 | 0.4166          | 0.4111    | 0.5813 | 0.4816 | 0.9441   |
| 0.4128        | 8.0   | 4024 | 0.4124          | 0.4144    | 0.5879 | 0.4862 | 0.9448   |
| 0.4008        | 9.0   | 4527 | 0.4067          | 0.4194    | 0.5904 | 0.4904 | 0.9455   |
| 0.3983        | 10.0  | 5030 | 0.4056          | 0.4202    | 0.5916 | 0.4914 | 0.9456   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0