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metadata
license: cc-by-nc-sa-4.0
base_model: InstaDeepAI/nucleotide-transformer-2.5b-1000g
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: nucleotide-transformer-finetuned-lora-NucleotideTransformer
    results: []

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