BertGoodCommitPreprocessed – AI Model by AlexC98 | AlphaNeural AI | AlphaNeural AI

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AlexC98/
BertGoodCommitPreprocessed

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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BertGoodCommitPreprocessed

This model is a fine-tuned version of prajjwal1/bert-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5242
Accuracy: 0.8424

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: 1e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 200

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	24	0.5858	0.6788
No log	2.0	48	0.5640	0.7273
No log	3.0	72	0.5381	0.7394
No log	4.0	96	0.5246	0.7394
No log	5.0	120	0.5214	0.7394
No log	6.0	144	0.5093	0.7394
No log	7.0	168	0.4986	0.7515
No log	8.0	192	0.5131	0.7455
No log	9.0	216	0.5093	0.7697
No log	10.0	240	0.5064	0.7758
No log	11.0	264	0.5069	0.7697
No log	12.0	288	0.4774	0.7818
No log	13.0	312	0.5096	0.7879
No log	14.0	336	0.4933	0.7939
No log	15.0	360	0.4740	0.7939
No log	16.0	384	0.4787	0.7939
No log	17.0	408	0.4675	0.8
No log	18.0	432	0.4971	0.8121
No log	19.0	456	0.4935	0.8303
No log	20.0	480	0.4947	0.8121
0.3574	21.0	504	0.4968	0.8242
0.3574	22.0	528	0.5158	0.8303
0.3574	23.0	552	0.5146	0.8061
0.3574	24.0	576	0.4963	0.8303
0.3574	25.0	600	0.5024	0.8182
0.3574	26.0	624	0.5069	0.8242
0.3574	27.0	648	0.5242	0.8424

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3