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checkpoints_xnli

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

  • Loss: 0.4345
  • Accuracy: 0.8473

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: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4929 1.0 11045 0.4551 0.8217
0.408 2.0 22090 0.4308 0.8358
0.3093 3.0 33135 0.4345 0.8473

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Safetensors
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Finetuned from

Dataset used to train PJM124/checkpoints_xnli

Evaluation results