gut_1024-finetuned-lora-NT-2.5b-1000g – AI Model by LiukG | AlphaNeural AI

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LiukG/
gut_1024-finetuned-lora-NT-2.5b-1000g

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text-classification

generated_from_trainer

InstaDeepAI/nucleotide-transformer-2.5b-1000g

cc-by-nc-sa-4.0

autotrain_compatible

endpoints_compatible

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nucleotide-transformer-finetuned-lora-NucleotideTransformer

This model is a fine-tuned version of InstaDeepAI/nucleotide-transformer-2.5b-1000g on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6900
F1: 0.8402
Mcc Score: 0.5492
Accuracy: 0.7891

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: 3
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
1.3108	0.05	100	0.8230	0.6491	0.3170	0.6367
0.9207	0.11	200	0.6670	0.6016	0.2636	0.6016
0.6734	0.16	300	0.5539	0.8190	0.4873	0.7617
0.7133	0.21	400	0.5834	0.8148	0.4994	0.7656
0.6225	0.26	500	0.8411	0.8343	0.5144	0.7656
0.8485	0.32	600	0.6813	0.7336	0.3999	0.6992
0.7567	0.37	700	0.6454	0.8504	0.5770	0.8008
0.5729	0.42	800	0.8756	0.7910	0.4676	0.7461
0.7708	0.47	900	0.6872	0.8303	0.5314	0.7812
0.6194	0.53	1000	0.6900	0.8402	0.5492	0.7891

Framework versions

Transformers 4.38.1
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2