roberta_ukr-psyop-6_3

This model is a fine-tuned version of youscan/ukr-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0326
  • Accuracy: 0.9929
  • Precision: 0.9951
  • Recall: 0.9906
  • F1-score: 0.9928
  • Matthews Corrcoef: 0.9857

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: 5e-05
  • train_batch_size: 14
  • eval_batch_size: 14
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 6

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1-score Matthews Corrcoef
0.0545 1.0 1787 0.0350 0.9904 0.9849 0.9961 0.9905 0.9809
0.0001 2.0 3574 0.0512 0.9925 0.9925 0.9925 0.9925 0.9851
0.0069 3.0 5361 0.0326 0.9929 0.9951 0.9906 0.9928 0.9857
0.0 4.0 7148 0.0714 0.9912 0.9874 0.9951 0.9913 0.9825
0.0 5.0 8935 0.0709 0.9925 0.9961 0.9890 0.9925 0.9851
0.0 6.0 10722 0.0629 0.9933 0.9932 0.9935 0.9933 0.9867

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
14
Safetensors
Model size
126M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Model tree for ProrabVasili/roberta_ukr-psyop-6_3

Finetuned
(4)
this model