results – AI Model by sumups-ai | AlphaNeural AI

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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results

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

Loss: 1.4578
Precision: 0.0060
Recall: 0.0286
F1: 0.0099
Accuracy: 0.4288

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	8	1.6449	0.0	0.0	0.0	0.3860
No log	2.0	16	1.5439	0.0014	0.0071	0.0023	0.4025
No log	3.0	24	1.4986	0.0068	0.0286	0.0110	0.4176
No log	4.0	32	1.4603	0.0033	0.0143	0.0054	0.4285
No log	5.0	40	1.4578	0.0060	0.0286	0.0099	0.4288

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2