baseline_nli_bert-large – AI Model by jalaluddin94 | AlphaNeural AI

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jalaluddin94/
baseline_nli_bert-large

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text-classification

generated_from_trainer

google-bert/bert-large-uncased

autotrain_compatible

endpoints_compatible

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baseline_nli_bert-large

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

Loss: 0.9293
Accuracy: 0.6163
Precision: 0.6163
Recall: 0.6163
F1 Score: 0.6185

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
1.0447	1.0	2583	0.9867	0.4602	0.4602	0.4602	0.4166
0.9632	2.0	5166	0.9132	0.5926	0.5926	0.5926	0.5965
0.9063	3.0	7749	0.8976	0.6076	0.6076	0.6076	0.6116
0.846	4.0	10332	0.8826	0.6218	0.6218	0.6218	0.6212
0.7975	5.0	12915	0.9189	0.6136	0.6136	0.6136	0.6169
0.7605	6.0	15498	0.9293	0.6163	0.6163	0.6163	0.6185

Framework versions

Transformers 4.32.1
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3