CSQA_roberta_large / README.md
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csqa_roberta_large
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metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: test-glue
    results: []

test-glue

This model is a fine-tuned version of FacebookAI/roberta-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6847
  • Accuracy: 0.7232

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 150
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.9984 304 0.9992 0.6224
1.352 1.9984 608 0.7015 0.7150
1.352 2.9984 912 0.6847 0.7232

Framework versions

  • Transformers 4.52.0.dev0
  • Pytorch 2.6.0+cu124
  • Datasets 3.5.2.dev0
  • Tokenizers 0.21.1