mus_promoter-finetuned-lora-NT-500m-1000g – AI Model by LiukG | AlphaNeural AI

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LiukG/
mus_promoter-finetuned-lora-NT-500m-1000g

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text-classification

generated_from_trainer

InstaDeepAI/nucleotide-transformer-500m-1000g

cc-by-nc-sa-4.0

autotrain_compatible

endpoints_compatible

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mus_promoter-finetuned-lora-NT-500m-1000g

This model is a fine-tuned version of InstaDeepAI/nucleotide-transformer-500m-1000g on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3065
F1: 0.9351
Mcc Score: 0.8414
Accuracy: 0.9219

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: 0.0005
train_batch_size: 8
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Mcc Score	Accuracy
0.6126	0.43	100	0.4697	0.8767	0.7135	0.8594
0.3854	0.85	200	0.2682	0.9296	0.8460	0.9219
0.4832	1.28	300	0.2444	0.9296	0.8460	0.9219
0.3536	1.71	400	0.3433	0.9167	0.8113	0.9062
0.3215	2.14	500	0.3475	0.9351	0.8414	0.9219
0.2961	2.56	600	0.2347	0.9231	0.8108	0.9062
0.2742	2.99	700	0.3438	0.9333	0.8395	0.9219
0.2375	3.42	800	0.3448	0.9351	0.8414	0.9219
0.2438	3.85	900	0.2789	0.9351	0.8414	0.9219
0.2104	4.27	1000	0.3065	0.9351	0.8414	0.9219

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2