wnc-pretrain – AI Model by charisgao | AlphaNeural AI

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charisgao/
wnc-pretrain

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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pretrain_model

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

Loss: 0.6409
Precision: 0.6385
Recall: 0.6046
F1: 0.6211
Accuracy: 0.6354

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: 8
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.6994	0.0061	250	0.6909	0.5946	0.1740	0.2692	0.5296
0.6935	0.0122	500	0.6461	0.6368	0.5923	0.6138	0.6288
0.6862	0.0184	750	0.6710	0.6268	0.6416	0.6341	0.6313
0.6629	0.0245	1000	0.8414	0.5772	0.7777	0.6626	0.6056
0.6729	0.0306	1250	0.6509	0.6373	0.5992	0.6177	0.6306

Framework versions

Transformers 4.46.3
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3