albert-base-v2-finetuned-filtered-0609 – AI Model by YeRyeongLee | AlphaNeural AI

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YeRyeongLee/
albert-base-v2-finetuned-filtered-0609

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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albert-base-v2-finetuned-filtered-0609

This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2062
Accuracy: 0.9723
Precision: 0.9724
Recall: 0.9723
F1: 0.9723

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.2688	1.0	3180	0.2282	0.9560	0.9577	0.9560	0.9562
0.2268	2.0	6360	0.1909	0.9638	0.9640	0.9638	0.9638
0.1831	3.0	9540	0.2590	0.9572	0.9584	0.9572	0.9572
0.1588	4.0	12720	0.1752	0.9673	0.9678	0.9673	0.9673
0.0972	5.0	15900	0.1868	0.9695	0.9696	0.9695	0.9695
0.0854	6.0	19080	0.2042	0.9701	0.9707	0.9701	0.9702
0.0599	7.0	22260	0.1793	0.9748	0.9749	0.9748	0.9749
0.0389	8.0	25440	0.1996	0.9742	0.9743	0.9742	0.9742
0.0202	9.0	28620	0.2188	0.9723	0.9726	0.9723	0.9724
0.0152	10.0	31800	0.2062	0.9723	0.9724	0.9723	0.9723

Framework versions

Transformers 4.19.2
Pytorch 1.9.1+cu111
Datasets 1.16.1
Tokenizers 0.12.1