metadata

language:
  - en
license: mit
tags:
  - generated_from_trainer
datasets:
  - nyu-mll/glue
metrics:
  - accuracy
model-index:
  - name: roberta-base_mnli_bc
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: GLUE MNLI
          type: glue
          args: mnli
        metrics:
          - type: accuracy
            value: 0.9583768461882739
            name: Accuracy

roberta-base_mnli_bc

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

Loss: 0.2125
Accuracy: 0.9584

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2015	1.0	16363	0.1820	0.9470
0.1463	2.0	32726	0.1909	0.9559
0.0768	3.0	49089	0.2117	0.9585

Framework versions

Transformers 4.13.0
Pytorch 1.10.1+cu111
Datasets 1.17.0
Tokenizers 0.10.3