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gyr66/
RoBERTa-ext-large-lora-chinese-finetuned-ner

Name: RoBERTa-ext-large-lora-chinese-finetuned-ner
Availability: InStock

safetensors

generated_from_trainer

hfl/chinese-roberta-wwm-ext-large

finetune

apache-2.0

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

This model is a fine-tuned version of hfl/chinese-roberta-wwm-ext-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3762
Precision: 0.6284
Recall: 0.7311
F1: 0.6759
Accuracy: 0.9107

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: 0.001
train_batch_size: 8
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
0.5112	1.0	252	0.3440	0.5005	0.6105	0.5501	0.8940
0.283	2.0	504	0.3198	0.5363	0.6715	0.5963	0.9017
0.2373	3.0	756	0.3104	0.5506	0.7216	0.6246	0.9054
0.1995	4.0	1008	0.3210	0.5804	0.7236	0.6441	0.9092
0.1678	5.0	1260	0.3300	0.5828	0.7140	0.6418	0.9077
0.1435	6.0	1512	0.3274	0.5912	0.7173	0.6482	0.9104
0.1206	7.0	1764	0.3566	0.5964	0.7351	0.6585	0.9079
0.105	8.0	2016	0.3579	0.6065	0.7281	0.6618	0.9112
0.0925	9.0	2268	0.3645	0.6148	0.7382	0.6709	0.9103
0.0835	10.0	2520	0.3762	0.6284	0.7311	0.6759	0.9107

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0

gyr66/RoBERTa-ext-large-lora-chinese-finetuned-ner

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

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gyr66/
RoBERTa-ext-large-lora-chinese-finetuned-ner