baseline_nli_bert – AI Model by jalaluddin94 | AlphaNeural AI

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jalaluddin94/
baseline_nli_bert

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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baseline_nli_bert

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: 0.9280
Accuracy: 0.6063
Precision: 0.6063
Recall: 0.6063
F1 Score: 0.6088

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: 3e-06
train_batch_size: 4
eval_batch_size: 4
seed: 101
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1 Score
1.0366	1.0	2583	0.9579	0.5603	0.5603	0.5603	0.5638
0.9416	2.0	5166	0.9206	0.5826	0.5826	0.5826	0.5877
0.8889	3.0	7749	0.9085	0.5981	0.5981	0.5981	0.6025
0.8539	4.0	10332	0.9176	0.6054	0.6054	0.6054	0.6089
0.8323	5.0	12915	0.9201	0.6049	0.6049	0.6049	0.6066
0.811	6.0	15498	0.9280	0.6063	0.6063	0.6063	0.6088

Framework versions

Transformers 4.27.3
Pytorch 1.12.1
Datasets 2.11.0
Tokenizers 0.13.2