metadata

language:
  - en
license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: roberta-base-rte
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE RTE
          type: glue
          args: rte
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7581227436823105

roberta-base-rte

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

Loss: 0.6365
Accuracy: 0.7581

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
lr_scheduler_warmup_ratio: 0.06
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	156	0.7072	0.4729
No log	2.0	312	0.6958	0.5271
No log	3.0	468	0.6193	0.6462
0.6759	4.0	624	0.6046	0.7076
0.6759	5.0	780	0.6365	0.7581
0.6759	6.0	936	0.8975	0.7545
0.3194	7.0	1092	1.2031	0.7581
0.3194	8.0	1248	1.2942	0.7581

Framework versions

Transformers 4.20.0.dev0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1