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metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: xlm-roberta-large_product_classifier
    results: []

xlm-roberta-large_product_classifier

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

  • Loss: 1.3981
  • Accuracy: 0.8169

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 490 0.8869 0.7423
1.3297 2.0 980 0.7796 0.7798
0.7265 3.0 1470 0.7592 0.7872
0.5509 4.0 1960 0.8112 0.7949
0.4258 5.0 2450 0.8498 0.7875
0.3307 6.0 2940 0.8326 0.8036
0.2702 7.0 3430 0.8833 0.8066
0.2078 8.0 3920 0.9260 0.8066
0.1571 9.0 4410 0.9800 0.8087
0.1242 10.0 4900 1.0725 0.8043
0.0962 11.0 5390 1.2147 0.7946
0.0857 12.0 5880 1.1705 0.8123
0.0667 13.0 6370 1.2551 0.8041
0.052 14.0 6860 1.2762 0.8184
0.0414 15.0 7350 1.3442 0.8115
0.0313 16.0 7840 1.3510 0.8130
0.0247 17.0 8330 1.3754 0.8133
0.0158 18.0 8820 1.3915 0.8135
0.0162 19.0 9310 1.3975 0.8186
0.0109 20.0 9800 1.3981 0.8169

Framework versions

  • Transformers 4.48.0
  • Pytorch 2.5.1+cu124
  • Datasets 2.21.0
  • Tokenizers 0.21.0