robbert0210_lrate2.5 – AI Model by Tommert25 | AlphaNeural AI

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Tommert25/
robbert0210_lrate2.5

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token-classification

generated_from_trainer

Tommert25/robbert2909_lrate7.5

autotrain_compatible

endpoints_compatible

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robbert0210_lrate2.5

This model is a fine-tuned version of Tommert25/robbert2909_lrate7.5 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6768
Precisions: 0.8111
Recall: 0.7885
F-measure: 0.7986
Accuracy: 0.9113

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: 2.5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Precisions	Recall	F-measure	Accuracy
0.054	1.0	942	0.6914	0.8256	0.7674	0.7846	0.9065
0.0568	2.0	1884	0.7397	0.8402	0.7902	0.8075	0.9099
0.0423	3.0	2826	0.6768	0.8111	0.7885	0.7986	0.9113
0.0293	4.0	3768	0.7276	0.8138	0.7879	0.7997	0.9142
0.0195	5.0	4710	0.7553	0.8036	0.7902	0.7951	0.9109
0.0129	6.0	5652	0.7606	0.8061	0.7962	0.7999	0.9100
0.0051	7.0	6594	0.7815	0.8039	0.7993	0.7996	0.9109
0.0104	8.0	7536	0.7743	0.8077	0.7986	0.8016	0.9121

Framework versions

Transformers 4.33.3
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3