CoolFace
Modelpublic

RonTon05/Revision_11_03_XLM_Lexical_MetaXLM_Q1-52K

sourceHugging Facemitupdated 7mo 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. -->

Revision1103XLMLexicalMetaXLMQ1-52K

This model is a fine-tuned version of phunganhsang/Revision_XLMRoBERTa_Lexical_Dataset_52k on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 2.6261
  • —Accuracy: 0.6702
  • —F1: 0.6700

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: 2e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 5

Training results

Training LossEpochStepValidation LossAccuracyF1
No log0.20331000.53910.80420.8011
No log0.40652000.62160.78740.7850
No log0.60983000.78040.79320.7910
No log0.81304000.95580.71290.7128
0.22471.01635001.90120.55370.5443
0.22471.21956002.31940.55650.5471
0.22471.42287002.25560.55360.5439
0.22471.62608002.24960.57250.5656
0.22471.82939002.76060.54640.5355
0.07312.032510002.93510.55690.5477
0.07312.235811002.47030.66710.6668
0.07312.439012002.35440.66290.6625
0.07312.642313002.29190.66820.6679
0.07312.845514002.03670.71210.7120
0.03613.048815002.56260.64880.6480
0.03613.252016002.78920.64350.6424
0.03613.455317002.57840.66230.6619
0.03613.658518002.76570.64360.6425
0.03613.861819002.34330.68840.6884
0.02324.065020002.45730.69320.6932
0.02324.268321002.89290.64990.6492
0.02324.471522002.66760.66600.6657
0.02324.674823002.65640.66810.6678
0.02324.878024002.62610.67020.6700

Framework versions

  • —Transformers 5.3.0
  • —Pytorch 2.9.0+cu126
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2