metadata

base_model: vinai/bertweet-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: bertweetB_15epoch
    results: []

bertweetB_15epoch

This model is a fine-tuned version of vinai/bertweet-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1645
Accuracy: 0.77
Precision: 0.2476
Recall: 0.3173
F1: 0.2757

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: 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: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	217	0.1306	0.8571	0.0	0.0	0.0
No log	2.0	434	0.1295	0.8571	0.0	0.0	0.0
0.1937	3.0	651	0.1268	0.8571	0.0	0.0	0.0
0.1937	4.0	868	0.1227	0.8593	0.3712	0.0701	0.1179
0.1473	5.0	1085	0.1307	0.765	0.2292	0.4354	0.3003
0.1473	6.0	1302	0.1270	0.7964	0.2457	0.3469	0.2877
0.1018	7.0	1519	0.1398	0.7607	0.2276	0.4354	0.2978
0.1018	8.0	1736	0.1449	0.7821	0.2323	0.3506	0.2786
0.1018	9.0	1953	0.1408	0.7843	0.2681	0.3764	0.3127
0.0648	10.0	2170	0.1535	0.78	0.2455	0.2878	0.2634
0.0648	11.0	2387	0.1585	0.7593	0.2375	0.3911	0.2954
0.0396	12.0	2604	0.1591	0.7757	0.2642	0.3100	0.2809
0.0396	13.0	2821	0.1670	0.7614	0.2347	0.3432	0.2774
0.0284	14.0	3038	0.1623	0.7793	0.2561	0.3026	0.2745
0.0284	15.0	3255	0.1645	0.77	0.2476	0.3173	0.2757

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1