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rm23_ctry_v2lr

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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metadata
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: rm23_ctry_v2lr
    results: []

rm23_ctry_v2lr

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

  • Loss: 0.2185
  • F1: 0.9566

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: 16
  • eval_batch_size: 8
  • 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 F1
0.2088 1.0 17996 0.1879 0.9311
0.1477 2.0 35992 0.1772 0.9467
0.1006 3.0 53988 0.2101 0.9508
0.0615 4.0 71984 0.2185 0.9566

Framework versions

  • Transformers 4.29.1
  • Pytorch 1.13.1
  • Datasets 2.12.0
  • Tokenizers 0.13.3