metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
model-index:
  - name: roberta-base-finetuned-ner-kmeans-twitter
    results: []

roberta-base-finetuned-ner-kmeans-twitter

This model is a fine-tuned version of ArBert/roberta-base-finetuned-ner on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6645
Precision: 0.6885
Recall: 0.7665
F1: 0.7254

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
No log	1.0	245	0.2820	0.6027	0.7543	0.6700
No log	2.0	490	0.2744	0.6308	0.7864	0.7000
0.2301	3.0	735	0.2788	0.6433	0.7637	0.6984
0.2301	4.0	980	0.3255	0.6834	0.7221	0.7022
0.1153	5.0	1225	0.3453	0.6686	0.7439	0.7043
0.1153	6.0	1470	0.3988	0.6797	0.7420	0.7094
0.0617	7.0	1715	0.4711	0.6702	0.7259	0.6969
0.0617	8.0	1960	0.4904	0.6904	0.7505	0.7192
0.0328	9.0	2205	0.5088	0.6591	0.7713	0.7108
0.0328	10.0	2450	0.5709	0.6468	0.7788	0.7067
0.019	11.0	2695	0.5570	0.6642	0.7533	0.7059
0.019	12.0	2940	0.5574	0.6899	0.7656	0.7258
0.0131	13.0	3185	0.5858	0.6952	0.7609	0.7265
0.0131	14.0	3430	0.6239	0.6556	0.7826	0.7135
0.0074	15.0	3675	0.5931	0.6825	0.7599	0.7191
0.0074	16.0	3920	0.6364	0.6785	0.7580	0.7161
0.005	17.0	4165	0.6437	0.6855	0.7580	0.7199
0.005	18.0	4410	0.6610	0.6779	0.7599	0.7166
0.0029	19.0	4655	0.6625	0.6853	0.7656	0.7232
0.0029	20.0	4900	0.6645	0.6885	0.7665	0.7254

Framework versions

Transformers 4.16.2
Pytorch 1.10.0+cu111
Datasets 1.18.3
Tokenizers 0.11.0