Edit model card

XLM-RoBERTa-xtreme-en-token-drift

This model is a fine-tuned version of xlm-roberta-base on the xtreme_en_token_drift dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2802
  • Accuracy: 0.9089
  • F1: 0.7613

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
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.6398 1.0 161 0.3421 0.8973 0.7111
0.3268 2.0 322 0.2846 0.9097 0.7611
0.2701 3.0 483 0.2802 0.9089 0.7613

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1
Downloads last month
2
Hosted inference API
Token Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.

Evaluation results