LiukG's picture
End of training
5eb2123 verified
metadata
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-v2-250m-multi-species
tags:
  - generated_from_trainer
metrics:
  - f1
  - matthews_correlation
  - accuracy
model-index:
  - name: gut_1024b-finetuned-lora-v2-250m-multi-species
    results: []

gut_1024b-finetuned-lora-v2-250m-multi-species

This model is a fine-tuned version of InstaDeepAI/nucleotide-transformer-v2-250m-multi-species on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4815
  • F1: 0.8414
  • Matthews Correlation: 0.5610
  • Accuracy: 0.7880
  • F1 Score: 0.8414

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 Matthews Correlation Accuracy F1 Score
0.682 0.02 100 0.5545 0.8132 0.4597 0.7369 0.8132
0.6379 0.04 200 0.6119 0.7498 0.4244 0.7154 0.7498
0.5973 0.05 300 0.5226 0.8221 0.5154 0.7707 0.8221
0.5451 0.07 400 0.5159 0.8244 0.5010 0.7521 0.8244
0.5538 0.09 500 0.5538 0.8102 0.5043 0.7648 0.8102
0.549 0.11 600 0.5220 0.8258 0.5188 0.7715 0.8258
0.4887 0.12 700 0.4940 0.8330 0.5317 0.7728 0.8330
0.4893 0.14 800 0.4951 0.8352 0.5519 0.7872 0.8352
0.4794 0.16 900 0.5008 0.8443 0.5687 0.7893 0.8443
0.5437 0.18 1000 0.4815 0.8414 0.5610 0.7880 0.8414

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2