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metadata
license: mit
base_model: xlm-roberta-base
tags:
  - generated_from_trainer
model-index:
  - name: xlm-roberta-base-finetuned-Adapter-ar-mlm-0.15-large-29OCT
    results: []

xlm-roberta-base-finetuned-Adapter-ar-mlm-0.15-large-29OCT

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

  • Loss: 2.0107
  • Model Preparation Time: 0.0044

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: 0.0001
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Model Preparation Time
3.5857 0.4703 1000 2.9678 0.0044
2.8254 0.9407 2000 2.5072 0.0044
2.5882 1.4110 3000 2.3254 0.0044
2.4612 1.8814 4000 2.2290 0.0044
2.3731 2.3517 5000 2.1540 0.0044
2.316 2.8221 6000 2.1089 0.0044
2.2806 3.2924 7000 2.0712 0.0044
2.2416 3.7628 8000 2.0418 0.0044
2.21 4.2331 9000 2.0209 0.0044
2.1977 4.7035 10000 2.0107 0.0044

Framework versions

  • Transformers 4.43.4
  • Pytorch 2.1.1+cu121
  • Datasets 3.0.2
  • Tokenizers 0.19.1