TenaliAI-FinTech-v2 – AI Model by credentek | AlphaNeural AI

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credentek/
TenaliAI-FinTech-v2

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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TenaliAI-FinTech-v2

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

Loss: 0.0042

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
No log	1.0	14	3.8371
No log	2.0	28	3.0541
No log	3.0	42	1.6426
No log	4.0	56	0.7499
No log	5.0	70	0.2611
No log	6.0	84	0.0687
No log	7.0	98	0.0198
No log	8.0	112	0.0085
No log	9.0	126	0.0055
No log	10.0	140	0.0042

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1