lewtun's picture
lewtun HF staff
End of training
38662ea
metadata
license: mit
tags:
  - generated_from_trainer
datasets:
  - clinc_oos
metrics:
  - accuracy
model-index:
  - name: roberta-large-finetuned-clinc-314
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: clinc_oos
          type: clinc_oos
          args: plus
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.932258064516129

roberta-large-finetuned-clinc-314

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

  • Loss: 0.7983
  • Accuracy: 0.9323

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: 16
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: sagemaker_data_parallel
  • num_devices: 8
  • total_train_batch_size: 128
  • total_eval_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
5.0674 1.0 120 5.0406 0.0061
4.566 2.0 240 3.0712 0.7316
2.1553 3.0 360 0.7983 0.9323

Framework versions

  • Transformers 4.12.3
  • Pytorch 1.9.1
  • Datasets 1.15.1
  • Tokenizers 0.10.3