tab-anonymizer-v2 – AI Model by madaanpulkit | AlphaNeural AI

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madaanpulkit/
tab-anonymizer-v2

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token-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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tab-anonymizer-v2

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

Loss: 0.1163
Recall Direct: 0.9069
Recall Quasi: 0.8510
Precision Direct: 0.9623
Precision Quasi: 0.8630

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Recall Direct	Recall Quasi	Precision Direct	Precision Quasi
No log	1.0	64	0.2676	0.0	0.6497	nan	0.7835
No log	2.0	128	0.1674	0.7479	0.7933	0.7118	0.8331
No log	3.0	192	0.1350	0.8173	0.8374	0.9271	0.8501
No log	4.0	256	0.1271	0.8714	0.8428	0.9381	0.8606
No log	5.0	320	0.1197	0.9002	0.8456	0.9333	0.8563
No log	6.0	384	0.1176	0.8985	0.8351	0.9499	0.8644
No log	7.0	448	0.1212	0.8934	0.8079	0.9670	0.8697
0.2055	8.0	512	0.1171	0.9069	0.8538	0.9606	0.8605
0.2055	9.0	576	0.1166	0.9069	0.8613	0.9623	0.8543
0.2055	10.0	640	0.1163	0.9069	0.8510	0.9623	0.8630

Framework versions

Transformers 4.32.0
Pytorch 1.12.0
Datasets 2.10.1
Tokenizers 0.13.3