xlnet-base-cased_fold_1_binary_v1 – AI Model by elopezlopez | AlphaNeural AI

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xlnet-base-cased_fold_1_binary_v1

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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xlnet-base-cased_fold_1_binary_v1

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

Loss: 1.7812
F1: 0.8161

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: 25

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	288	0.3938	0.8019
0.4444	2.0	576	0.3945	0.8086
0.4444	3.0	864	0.4738	0.8245
0.2504	4.0	1152	0.6641	0.8123
0.2504	5.0	1440	0.8714	0.7863
0.159	6.0	1728	0.9177	0.8179
0.0832	7.0	2016	1.1719	0.8129
0.0832	8.0	2304	1.2858	0.8146
0.046	9.0	2592	1.2557	0.8181
0.046	10.0	2880	1.3332	0.8033
0.0313	11.0	3168	1.2840	0.8112
0.0313	12.0	3456	1.4164	0.8175
0.0246	13.0	3744	1.3709	0.8143
0.0173	14.0	4032	1.4319	0.8179
0.0173	15.0	4320	1.5706	0.8195
0.0138	16.0	4608	1.6072	0.8230
0.0138	17.0	4896	1.7454	0.8192
0.0016	18.0	5184	1.7281	0.8099
0.0016	19.0	5472	1.7692	0.8151
0.0088	20.0	5760	1.7376	0.8132
0.0081	21.0	6048	1.7715	0.8086
0.0081	22.0	6336	1.7400	0.8152
0.0053	23.0	6624	1.7845	0.8099
0.0053	24.0	6912	1.8096	0.8150
0.0062	25.0	7200	1.7812	0.8161

Framework versions

Transformers 4.21.1
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1