BERT_Dec-6_tokenized – AI Model by Mozart-coder | AlphaNeural AI

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BERT_Dec-6_tokenized

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BERT_Dec-6_tokenized

This model is a fine-tuned version of armheb/DNA_bert_6 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0372

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: 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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.0625	1.0	273	0.0376
0.039	2.0	546	0.0375
0.0385	3.0	819	0.0358
0.0375	4.0	1092	0.0380
0.0374	5.0	1365	0.0387
0.0358	6.0	1638	0.0378
0.0363	7.0	1911	0.0381
0.0373	8.0	2184	0.0377
0.0362	9.0	2457	0.0373
0.037	10.0	2730	0.0380

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1