README.md

metadata

license: mit
base_model: facebook/esm2_t12_35M_UR50D
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: esm2_t12_35M_qlora_glycosylation_sites_2024-02-14_21-47-37
    results: []

esm2_t12_35M_qlora_glycosylation_sites_2024-02-14_21-47-37

This model is a fine-tuned version of facebook/esm2_t12_35M_UR50D on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0108
• Accuracy: 0.9990
• Precision: 0.3291
• Recall: 0.9951
• F1: 0.4946
• Auc: 0.9970
• Mcc: 0.5720

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: 0.0003701568055793089
• train_batch_size: 36
• eval_batch_size: 36
• seed: 8893
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Auc	Mcc
0.0125	1.0	16521	0.0108	0.9990	0.3291	0.9951	0.4946	0.9970	0.5720

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.1