philschmid / roberta-large-sst2

huggingface.co
Total runs: 172
24-hour runs: 0
7-day runs: -15
30-day runs: 77
Model's Last Updated: April 08 2022
text-classification

Introduction of roberta-large-sst2

Model Details of roberta-large-sst2

roberta-large-sst2

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

  • Loss: 0.1400
  • Accuracy: 0.9644
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: 3e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • distributed_type: sagemaker_data_parallel
  • num_devices: 8
  • total_train_batch_size: 256
  • total_eval_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 4
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.3688 1.0 264 0.1444 0.9564
0.1529 2.0 528 0.1502 0.9518
0.107 3.0 792 0.1388 0.9530
0.0666 4.0 1056 0.1400 0.9644
Framework versions
  • Transformers 4.17.0
  • Pytorch 1.10.2+cu113
  • Datasets 1.18.4
  • Tokenizers 0.11.6

Runs of philschmid roberta-large-sst2 on huggingface.co

172
Total runs
0
24-hour runs
0
3-day runs
-15
7-day runs
77
30-day runs

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roberta-large-sst2 install

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