CoolFace
Modelpublic

iTroned/olid_no_bootstrap_3

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
0likes
Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>

olidnobootstrap_3

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5138
  • Accuracy Offensive: 0.8150
  • F1 Offensive: 0.8043
  • Accuracy Targeted: 0.7961
  • F1 Targeted: 0.7710
  • Accuracy Stance: 0.7711
  • F1 Stance: 0.7229

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
  • trainbatchsize: 32
  • evalbatchsize: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 30

Training results

Training LossEpochStepValidation LossAccuracy OffensiveF1 OffensiveAccuracy TargetedF1 TargetedAccuracy StanceF1 Stance
No log1.03730.52820.79610.79990.76960.76020.75830.7232
0.58952.07460.51380.81500.80430.79610.77100.77110.7229
0.46083.011190.51820.80440.80480.78400.77240.77040.7579
0.46084.014920.54870.79530.79850.77340.76670.76660.7626

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.5.0+cu124
  • Datasets 3.0.1
  • Tokenizers 0.20.1