Roberta_vi_MLQA / README.md
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metadata
license: mit
tags:
  - generated_from_trainer
datasets:
  - mlqa
model-index:
  - name: Roberta_vi_MLQA
    results: []

Roberta_vi_MLQA

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

  • Loss: 2.3695

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • 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
2.5026 1.0 1928 2.5248
2.1866 2.0 3856 2.3501
1.9707 3.0 5784 2.3695

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3