Edit model card

ukr-roberta-base-finetuned-sarc

This model is a fine-tuned version of youscan/ukr-roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6150
  • Accuracy: 0.7983
  • Precision: 0.7945
  • Recall: 0.8048
  • F1: 0.7996
  • Roc Auc: 0.7983

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 Roc Auc
0.5014 1.0 538 0.4564 0.7844 0.8048 0.7509 0.7769 0.7844
0.4035 2.0 1076 0.4711 0.7918 0.8019 0.7751 0.7883 0.7918
0.314 3.0 1614 0.5327 0.7928 0.7933 0.7918 0.7926 0.7928
0.2431 4.0 2152 0.6150 0.7983 0.7945 0.8048 0.7996 0.7983

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
5
Safetensors
Model size
126M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Snizhanna/ukr-roberta-base-finetuned-sarc

Finetuned
(4)
this model

Space using Snizhanna/ukr-roberta-base-finetuned-sarc 1