This model is a fine-tuned version of cross-encoder/nli-distilroberta-base on the glue dataset. It achieves the following results on the evaluation set:

Loss: 0.8280
Matthews Correlation: 0.4957

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Matthews Correlation
0.5646	1.0	535	0.6462	0.3422
0.4267	2.0	1070	0.5672	0.4422
0.3354	3.0	1605	0.6441	0.4698
0.2723	4.0	2140	0.7464	0.4670
0.2204	5.0	2675	0.8280	0.4957

Framework versions

Transformers 4.25.1
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2

ShirinP/nli-distilroberta-base-finetuned-cola

nli-distilroberta-base-finetuned-cola

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ShirinP/
nli-distilroberta-base-finetuned-cola